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  "cells": [
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      "execution_count": 1,
      "metadata": {
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          "text": [
            "Collecting sentencepiece\n",
            "  Downloading sentencepiece-0.1.96-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.2 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.2 MB 5.0 MB/s \n",
            "\u001b[?25hInstalling collected packages: sentencepiece\n",
            "Successfully installed sentencepiece-0.1.96\n",
            "Collecting transformers\n",
            "  Downloading transformers-4.19.2-py3-none-any.whl (4.2 MB)\n",
            "\u001b[K     |████████████████████████████████| 4.2 MB 5.1 MB/s \n",
            "\u001b[?25hRequirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers) (2019.12.20)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.7/dist-packages (from transformers) (21.3)\n",
            "Collecting pyyaml>=5.1\n",
            "  Downloading PyYAML-6.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (596 kB)\n",
            "\u001b[K     |████████████████████████████████| 596 kB 52.0 MB/s \n",
            "\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from transformers) (2.23.0)\n",
            "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from transformers) (4.11.3)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from transformers) (1.21.6)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from transformers) (3.7.0)\n",
            "Collecting huggingface-hub<1.0,>=0.1.0\n",
            "  Downloading huggingface_hub-0.6.0-py3-none-any.whl (84 kB)\n",
            "\u001b[K     |████████████████████████████████| 84 kB 2.4 MB/s \n",
            "\u001b[?25hCollecting tokenizers!=0.11.3,<0.13,>=0.11.1\n",
            "  Downloading tokenizers-0.12.1-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (6.6 MB)\n",
            "\u001b[K     |████████████████████████████████| 6.6 MB 26.6 MB/s \n",
            "\u001b[?25hRequirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.7/dist-packages (from transformers) (4.64.0)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0,>=0.1.0->transformers) (4.2.0)\n",
            "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging>=20.0->transformers) (3.0.9)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->transformers) (3.8.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (2021.10.8)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (2.10)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (3.0.4)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (1.24.3)\n",
            "Installing collected packages: pyyaml, tokenizers, huggingface-hub, transformers\n",
            "  Attempting uninstall: pyyaml\n",
            "    Found existing installation: PyYAML 3.13\n",
            "    Uninstalling PyYAML-3.13:\n",
            "      Successfully uninstalled PyYAML-3.13\n",
            "Successfully installed huggingface-hub-0.6.0 pyyaml-6.0 tokenizers-0.12.1 transformers-4.19.2\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.7/dist-packages (1.11.0+cu113)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch) (4.2.0)\n",
            "Collecting rich[jupyter]\n",
            "  Downloading rich-12.4.1-py3-none-any.whl (231 kB)\n",
            "\u001b[K     |████████████████████████████████| 231 kB 4.8 MB/s \n",
            "\u001b[?25hCollecting commonmark<0.10.0,>=0.9.0\n",
            "  Downloading commonmark-0.9.1-py2.py3-none-any.whl (51 kB)\n",
            "\u001b[K     |████████████████████████████████| 51 kB 9.5 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pygments<3.0.0,>=2.6.0 in /usr/local/lib/python3.7/dist-packages (from rich[jupyter]) (2.6.1)\n",
            "Requirement already satisfied: typing-extensions<5.0,>=4.0.0 in /usr/local/lib/python3.7/dist-packages (from rich[jupyter]) (4.2.0)\n",
            "Requirement already satisfied: ipywidgets<8.0.0,>=7.5.1 in /usr/local/lib/python3.7/dist-packages (from rich[jupyter]) (7.7.0)\n",
            "Requirement already satisfied: ipython>=4.0.0 in /usr/local/lib/python3.7/dist-packages (from ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (5.5.0)\n",
            "Requirement already satisfied: ipykernel>=4.5.1 in /usr/local/lib/python3.7/dist-packages (from ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (4.10.1)\n",
            "Requirement already satisfied: widgetsnbextension~=3.6.0 in /usr/local/lib/python3.7/dist-packages (from ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (3.6.0)\n",
            "Requirement already satisfied: traitlets>=4.3.1 in /usr/local/lib/python3.7/dist-packages (from ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (5.1.1)\n",
            "Requirement already satisfied: ipython-genutils~=0.2.0 in /usr/local/lib/python3.7/dist-packages (from ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (0.2.0)\n",
            "Requirement already satisfied: jupyterlab-widgets>=1.0.0 in /usr/local/lib/python3.7/dist-packages (from ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (1.1.0)\n",
            "Requirement already satisfied: nbformat>=4.2.0 in /usr/local/lib/python3.7/dist-packages (from ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (5.4.0)\n",
            "Requirement already satisfied: tornado>=4.0 in /usr/local/lib/python3.7/dist-packages (from ipykernel>=4.5.1->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (5.1.1)\n",
            "Requirement already satisfied: jupyter-client in /usr/local/lib/python3.7/dist-packages (from ipykernel>=4.5.1->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (5.3.5)\n",
            "Requirement already satisfied: simplegeneric>0.8 in /usr/local/lib/python3.7/dist-packages (from ipython>=4.0.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (0.8.1)\n",
            "Requirement already satisfied: pickleshare in /usr/local/lib/python3.7/dist-packages (from ipython>=4.0.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (0.7.5)\n",
            "Requirement already satisfied: decorator in /usr/local/lib/python3.7/dist-packages (from ipython>=4.0.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (4.4.2)\n",
            "Requirement already satisfied: prompt-toolkit<2.0.0,>=1.0.4 in /usr/local/lib/python3.7/dist-packages (from ipython>=4.0.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (1.0.18)\n",
            "Requirement already satisfied: pexpect in /usr/local/lib/python3.7/dist-packages (from ipython>=4.0.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (4.8.0)\n",
            "Requirement already satisfied: setuptools>=18.5 in /usr/local/lib/python3.7/dist-packages (from ipython>=4.0.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (57.4.0)\n",
            "Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.7/dist-packages (from nbformat>=4.2.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (2.15.3)\n",
            "Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.7/dist-packages (from nbformat>=4.2.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (4.3.3)\n",
            "Requirement already satisfied: jupyter-core in /usr/local/lib/python3.7/dist-packages (from nbformat>=4.2.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (4.10.0)\n",
            "Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.7/dist-packages (from jsonschema>=2.6->nbformat>=4.2.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (0.18.1)\n",
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            "Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.7/dist-packages (from jsonschema>=2.6->nbformat>=4.2.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (21.4.0)\n",
            "Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.7/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=4.2.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (3.8.0)\n",
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            "Requirement already satisfied: six>=1.9.0 in /usr/local/lib/python3.7/dist-packages (from prompt-toolkit<2.0.0,>=1.0.4->ipython>=4.0.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (1.15.0)\n",
            "Requirement already satisfied: notebook>=4.4.1 in /usr/local/lib/python3.7/dist-packages (from widgetsnbextension~=3.6.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (5.3.1)\n",
            "Requirement already satisfied: Send2Trash in /usr/local/lib/python3.7/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (1.8.0)\n",
            "Requirement already satisfied: terminado>=0.8.1 in /usr/local/lib/python3.7/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (0.13.3)\n",
            "Requirement already satisfied: nbconvert in /usr/local/lib/python3.7/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (5.6.1)\n",
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            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from jupyter-client->ipykernel>=4.5.1->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (2.8.2)\n",
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            "Requirement already satisfied: bleach in /usr/local/lib/python3.7/dist-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (5.0.0)\n",
            "Requirement already satisfied: webencodings in /usr/local/lib/python3.7/dist-packages (from bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets<8.0.0,>=7.5.1->rich[jupyter]) (0.5.1)\n",
            "Installing collected packages: commonmark, rich\n",
            "Successfully installed commonmark-0.9.1 rich-12.4.1\n",
            "\u001b[K     |████████████████████████████████| 1.8 MB 5.0 MB/s \n",
            "\u001b[K     |████████████████████████████████| 145 kB 73.9 MB/s \n",
            "\u001b[K     |████████████████████████████████| 181 kB 69.8 MB/s \n",
            "\u001b[K     |████████████████████████████████| 63 kB 2.0 MB/s \n",
            "\u001b[?25h  Building wheel for pathtools (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: You can find your API key in your browser here: https://wandb.ai/authorize\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Paste an API key from your profile and hit enter, or press ctrl+c to quit: \n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n"
          ]
        }
      ],
      "source": [
        "\n",
        "!pip install sentencepiece\n",
        "!pip install transformers\n",
        "!pip install torch\n",
        "!pip install rich[jupyter]\n",
        "!pip install wandb -q\n",
        "import wandb\n",
        "!wandb login\n",
        "\n",
        "# Importing libraries\n",
        "import os\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import torch\n",
        "import torch.nn.functional as F\n",
        "from torch.utils.data import Dataset, DataLoader, RandomSampler, SequentialSampler\n",
        "import os\n",
        "\n",
        "# Importing the T5 modules from huggingface/transformers\n",
        "from transformers import T5Tokenizer, T5ForConditionalGeneration\n",
        "\n",
        "# rich: for a better display on terminal\n",
        "from rich.table import Column, Table\n",
        "from rich import box\n",
        "from rich.console import Console\n",
        "\n",
        "# define a rich console logger\n",
        "console = Console(record=True)\n",
        "\n",
        "# to display dataframe in ASCII format\n",
        "def display_df(df):\n",
        "    \"\"\"display dataframe in ASCII format\"\"\"\n",
        "\n",
        "    console = Console()\n",
        "    table = Table(\n",
        "        Column(\"review_body\", justify=\"center\"),\n",
        "        Column(\"review_headline\", justify=\"center\"),\n",
        "        title=\"Sample Data\",\n",
        "        pad_edge=False,\n",
        "        box=box.ASCII,\n",
        "    )\n",
        "\n",
        "    for i, row in enumerate(df.values.tolist()):\n",
        "        table.add_row(row[0], row[1])\n",
        "\n",
        "    console.print(table)\n",
        "\n",
        "# training logger to log training progress\n",
        "training_logger = Table(\n",
        "    Column(\"Epoch\", justify=\"center\"),\n",
        "    Column(\"Steps\", justify=\"center\"),\n",
        "    Column(\"Loss\", justify=\"center\"),\n",
        "    title=\"Training Status\",\n",
        "    pad_edge=False,\n",
        "    box=box.ASCII,\n",
        ")\n",
        "\n",
        "# Setting up the device for GPU usage\n",
        "from torch import cuda\n",
        "device = 'cuda' if cuda.is_available() else 'cpu'"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xg7Uff9xalHA",
        "outputId": "87e5d081-1a3e-46ee-c43e-33a84a4a0ede"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "class ReviewDataSet(Dataset):\n",
        "    \n",
        "\n",
        "    def __init__(\n",
        "        self, dataframe, tokenizer, source_len, target_len, review_body, review_headline\n",
        "    ):\n",
        "        \n",
        "        self.tokenizer = tokenizer\n",
        "        self.data = dataframe\n",
        "        self.source_len = source_len\n",
        "        self.summ_len = target_len\n",
        "        self.review_headline = self.data[review_headline]\n",
        "        self.review_body = self.data[review_body]\n",
        "\n",
        "    def __len__(self):\n",
        "        \"\"\"returns the length of dataframe\"\"\"\n",
        "\n",
        "        return len(self.review_headline)\n",
        "\n",
        "    def __getitem__(self, index):\n",
        "        \"\"\"return the input ids, attention masks and target ids\"\"\"\n",
        "\n",
        "        source_text = str(self.review_body[index])\n",
        "        target_text = str(self.review_headline[index])\n",
        "\n",
        "        # cleaning data to ensure data is in string type\n",
        "        source_text = \" \".join(source_text.split())\n",
        "        target_text = \" \".join(target_text.split())\n",
        "\n",
        "        source = self.tokenizer.batch_encode_plus(\n",
        "            [source_text],\n",
        "            max_length=self.source_len,\n",
        "            pad_to_max_length=True,\n",
        "            truncation=True,\n",
        "            padding=\"max_length\",\n",
        "            return_tensors=\"pt\",\n",
        "        )\n",
        "        target = self.tokenizer.batch_encode_plus(\n",
        "            [target_text],\n",
        "            max_length=self.summ_len,\n",
        "            pad_to_max_length=True,\n",
        "            truncation=True,\n",
        "            padding=\"max_length\",\n",
        "            return_tensors=\"pt\",\n",
        "        )\n",
        "\n",
        "        source_ids = source[\"input_ids\"].squeeze()\n",
        "        source_mask = source[\"attention_mask\"].squeeze()\n",
        "        target_ids = target[\"input_ids\"].squeeze()\n",
        "        target_mask = target[\"attention_mask\"].squeeze()\n",
        "\n",
        "        return {\n",
        "            \"source_ids\": source_ids.to(dtype=torch.long),\n",
        "            \"source_mask\": source_mask.to(dtype=torch.long),\n",
        "            \"target_ids\": target_ids.to(dtype=torch.long),\n",
        "            \"target_ids_y\": target_ids.to(dtype=torch.long),\n",
        "        }"
      ],
      "metadata": {
        "id": "E59HsO_vBZP9"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def train(epoch, tokenizer, model, device, loader, optimizer):\n",
        "    wandb.init()\n",
        "    model.train()\n",
        "    for _, data in enumerate(loader, 0):\n",
        "        y = data[\"target_ids\"].to(device, dtype=torch.long)\n",
        "        y_ids = y[:, :-1].contiguous()\n",
        "        lm_labels = y[:, 1:].clone().detach()\n",
        "        lm_labels[y[:, 1:] == tokenizer.pad_token_id] = -100\n",
        "        ids = data[\"source_ids\"].to(device, dtype=torch.long)\n",
        "        mask = data[\"source_mask\"].to(device, dtype=torch.long)\n",
        "\n",
        "        outputs = model(\n",
        "            input_ids=ids,\n",
        "            attention_mask=mask,\n",
        "            decoder_input_ids=y_ids,\n",
        "            labels=lm_labels,\n",
        "        )\n",
        "        loss = outputs[0]\n",
        "\n",
        "        if _ % 10 == 0:\n",
        "            training_logger.add_row(str(epoch), str(_), str(loss))\n",
        "            console.print(training_logger)\n",
        "            wandb.log({\"Training Loss\": loss.item()})\n",
        "\n",
        "        optimizer.zero_grad()\n",
        "        loss.backward()\n",
        "        optimizer.step()"
      ],
      "metadata": {
        "id": "ng293QKxCFz1"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def validate(epoch, tokenizer, model, device, loader):\n",
        "\n",
        "  \n",
        "  model.eval()\n",
        "  predictions = []\n",
        "  actuals = []\n",
        "  with torch.no_grad():\n",
        "      for _, data in enumerate(loader, 0):\n",
        "          y = data['target_ids'].to(device, dtype = torch.long)\n",
        "          ids = data['source_ids'].to(device, dtype = torch.long)\n",
        "          mask = data['source_mask'].to(device, dtype = torch.long)\n",
        "\n",
        "          generated_ids = model.generate(\n",
        "              input_ids = ids,\n",
        "              attention_mask = mask, \n",
        "              max_length=150, \n",
        "              num_beams=2,\n",
        "              repetition_penalty=2.5, \n",
        "              length_penalty=1.0, \n",
        "              early_stopping=True\n",
        "              )\n",
        "          preds = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=True) for g in generated_ids]\n",
        "          target = [tokenizer.decode(t, skip_special_tokens=True, clean_up_tokenization_spaces=True)for t in y]\n",
        "          if _%10==0:\n",
        "              console.print(f'Completed {_}')\n",
        "              \n",
        "\n",
        "          predictions.extend(preds)\n",
        "          actuals.extend(target)\n",
        "  return predictions, actuals"
      ],
      "metadata": {
        "id": "uPtyimAuCrw0"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def T5Trainer(\n",
        "    dataframe, source_text, target_text, model_params, output_dir=\"./outputs/\"\n",
        "):\n",
        "\n",
        "\n",
        "    # Set random seeds and deterministic pytorch for reproducibility\n",
        "    torch.manual_seed(model_params[\"SEED\"])  # pytorch random seed\n",
        "    np.random.seed(model_params[\"SEED\"])  # numpy random seed\n",
        "    torch.backends.cudnn.deterministic = True\n",
        "\n",
        "    # logging\n",
        "    console.log(f\"\"\"[Model]: Loading {model_params[\"MODEL\"]}...\\n\"\"\")\n",
        "\n",
        "    # tokenzier for encoding the text\n",
        "    tokenizer = T5Tokenizer.from_pretrained(model_params[\"MODEL\"])\n",
        "    \n",
        "    model = T5ForConditionalGeneration.from_pretrained(model_params[\"MODEL\"])\n",
        "    model = model.to(device)\n",
        "\n",
        "    # logging\n",
        "    console.log(f\"[Data]: Reading data...\\n\")\n",
        "\n",
        "   \n",
        "    dataframe = dataframe[[source_text, target_text]]\n",
        "    display_df(dataframe.head(2))\n",
        "\n",
        "    \n",
        "    train_size = 0.8\n",
        "    train_dataset = dataframe.sample(frac=train_size, random_state=model_params[\"SEED\"])\n",
        "    val_dataset = dataframe.drop(train_dataset.index).reset_index(drop=True)\n",
        "    train_dataset = train_dataset.reset_index(drop=True)\n",
        "\n",
        "    console.print(f\"FULL Dataset: {dataframe.shape}\")\n",
        "    console.print(f\"TRAIN Dataset: {train_dataset.shape}\")\n",
        "    console.print(f\"TEST Dataset: {val_dataset.shape}\\n\")\n",
        "\n",
        "    # Creating the Training and Validation dataset for further creation of Dataloader\n",
        "    training_set = ReviewDataSet(\n",
        "        train_dataset,\n",
        "        tokenizer,\n",
        "        model_params[\"MAX_SOURCE_TEXT_LENGTH\"],\n",
        "        model_params[\"MAX_TARGET_TEXT_LENGTH\"],\n",
        "        source_text,\n",
        "        target_text,\n",
        "    )\n",
        "    val_set = ReviewDataSet(\n",
        "        val_dataset,\n",
        "        tokenizer,\n",
        "        model_params[\"MAX_SOURCE_TEXT_LENGTH\"],\n",
        "        model_params[\"MAX_TARGET_TEXT_LENGTH\"],\n",
        "        source_text,\n",
        "        target_text,\n",
        "    )\n",
        "\n",
        "    # Defining the parameters for creation of dataloaders\n",
        "    train_params = {\n",
        "        \"batch_size\": model_params[\"TRAIN_BATCH_SIZE\"],\n",
        "        \"shuffle\": True,\n",
        "        \"num_workers\": 0,\n",
        "    }\n",
        "\n",
        "    val_params = {\n",
        "        \"batch_size\": model_params[\"VALID_BATCH_SIZE\"],\n",
        "        \"shuffle\": False,\n",
        "        \"num_workers\": 0,\n",
        "    }\n",
        "\n",
        "    training_loader = DataLoader(training_set, **train_params)\n",
        "    val_loader = DataLoader(val_set, **val_params)\n",
        "\n",
        "    optimizer = torch.optim.Adam(\n",
        "        params=model.parameters(), lr=model_params[\"LEARNING_RATE\"]\n",
        "    )\n",
        "\n",
        "    console.log(f\"[Initiating Fine Tuning]...\\n\")\n",
        "\n",
        "    for epoch in range(model_params[\"TRAIN_EPOCHS\"]):\n",
        "        train(epoch, tokenizer, model, device, training_loader, optimizer)\n",
        "\n",
        "    console.log(f\"[Saving Model]...\\n\")\n",
        "    # Saving the model after training\n",
        "    path = os.path.join(output_dir, \"model_files\")\n",
        "    model.save_pretrained(path)\n",
        "    tokenizer.save_pretrained(path)\n",
        "\n",
        "   \n",
        "    console.log(f\"[Initiating Validation]...\\n\")\n",
        "    for epoch in range(model_params[\"VAL_EPOCHS\"]):\n",
        "        predictions, actuals = validate(epoch, tokenizer, model, device, val_loader)\n",
        "        final_df = pd.DataFrame({\"Generated Text\": predictions, \"Actual Text\": actuals})\n",
        "        final_df.to_csv(os.path.join(output_dir, \"predictions.csv\"))\n",
        "\n",
        "    console.save_text(os.path.join(output_dir, \"logs.txt\"))\n",
        "\n",
        "    console.log(f\"[Validation Completed.]\\n\")\n",
        "    console.print(\n",
        "        f\"\"\"[Model] Model saved @ {os.path.join(output_dir, \"model_files\")}\\n\"\"\"\n",
        "    )\n",
        "    console.print(\n",
        "        f\"\"\"[Validation] Generation on Validation data saved @ {os.path.join(output_dir,'predictions.csv')}\\n\"\"\"\n",
        "    )"
      ],
      "metadata": {
        "id": "l2leBhEACyvF"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_params = {\n",
        "    \"MODEL\": \"t5-base\",  # model_type: t5-base\n",
        "    \"TRAIN_BATCH_SIZE\": 8,  # training batch size\n",
        "    \"VALID_BATCH_SIZE\": 8,  # validation batch size\n",
        "    \"TRAIN_EPOCHS\": 3,  # number of training epochs\n",
        "    \"VAL_EPOCHS\": 1,  # number of validation epochs\n",
        "    \"LEARNING_RATE\": 1e-4,  # learning rate\n",
        "    \"MAX_SOURCE_TEXT_LENGTH\": 512,  # max length of source text\n",
        "    \"MAX_TARGET_TEXT_LENGTH\": 50,  # max length of target text\n",
        "    \"SEED\": 42,  # set seed for reproducibility\n",
        "}"
      ],
      "metadata": {
        "id": "tUfdKazaESjp"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -q transformers datasets\n",
        "from google.colab import drive\n",
        "drive.mount('/gdrive')\n",
        "%cd /gdrive\n",
        "from datasets import load_dataset, Dataset\n",
        "import pandas as pd\n",
        "df2= pd.read_csv('My Drive/amazon_summary_data.csv')\n",
        "dataset = Dataset.from_pandas(df2)\n",
        "dataset = dataset.train_test_split(test_size=0.2)\n",
        "df=df2.head(2000)\n",
        "%cd /gdrive/MyDrive\n",
        "# T5 accepts prefix of the task to be performed:\n",
        "# Since we are summarizing, let's add summarize to source text as a prefix\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mPJkOgnjEUEe",
        "outputId": "92145760-85f5-48d6-8b16-d02f25cd6a2c"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[K     |████████████████████████████████| 346 kB 4.9 MB/s \n",
            "\u001b[K     |████████████████████████████████| 1.1 MB 56.8 MB/s \n",
            "\u001b[K     |████████████████████████████████| 140 kB 73.1 MB/s \n",
            "\u001b[K     |████████████████████████████████| 212 kB 55.3 MB/s \n",
            "\u001b[K     |████████████████████████████████| 127 kB 49.0 MB/s \n",
            "\u001b[K     |████████████████████████████████| 271 kB 63.8 MB/s \n",
            "\u001b[K     |████████████████████████████████| 94 kB 4.1 MB/s \n",
            "\u001b[K     |████████████████████████████████| 144 kB 82.1 MB/s \n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\u001b[0m\n",
            "\u001b[?25hMounted at /gdrive\n",
            "/gdrive\n",
            "/gdrive/MyDrive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "mG0IsTlkp4mI"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"review_body\"] = \"summarize: \" + df[\"review_body\"]\n",
        "\n",
        "T5Trainer(\n",
        "    dataframe=df,\n",
        "    source_text=\"review_body\", \n",
        "    target_text=\"review_headline\", \n",
        "    model_params=model_params,\n",
        "    output_dir=\"outputs\",\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "c806371b815f466188c852bc869b7e24",
            "b8c5718cd6e14a6ea9b3a8ed224f3f4d",
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            "aa7a2c2951ee415788f01817f86c1966",
            "31332d69e4c545b48375d02aaa6c77fa",
            "ccf05ef658c64caebb0b41fcdfa6c125",
            "1f79cb71cbfd4820bbfaa9192a954756",
            "b36538c3385543a3916cef368f8b0e9c",
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            "e087f39204d44a7bb706829777f4b062",
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            "cc457315b4c247d39269c6efdf51bddb",
            "38a1b5af008b4ef8a7b5cd982cd012dc",
            "9e2c90eaac254891821be67b948e2147",
            "bb02fd2a3a8746eba1ab5679bbdf24f6",
            "ecf27b001fbe498fa386123c3c0c3301",
            "a28b697689eb45beb34a34eac9fba160",
            "d58ce3eb1097406d8b35d9c4f152956d",
            "59db330b14b14c2a8e114e5463db8a97",
            "1cc412539abc4ca0a0104148189ceb17",
            "c4fa9ee5d2004389ba9fd6b3c9f02389",
            "1b7dc72fba074f78a1a159d77bba87ab",
            "4ac467daa12c43e2843def58768e435f",
            "c4b11df271984f1f8694a0d3ff3dcff8",
            "78713102c9db49e6bbadffbcaa8067e7",
            "1ed54ee5f8294344b58cbb1d4a92dfcf",
            "c2bc8a665b9b40b2aefe3f407ec79536",
            "5284a920ac7e4ea7915d05fae0a70115",
            "bd6a6232d18b4301ab068b36d142795b",
            "bedf87d70ac744cfa2a6bb373728ab82"
          ]
        },
        "id": "dUIOunkTQoY6",
        "outputId": "33748a36-a7a1-4c25-c331-1573a18f8a49"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            "/usr/local/lib/python3.7/dist-packages/transformers/models/t5/tokenization_t5.py:169: FutureWarning: This tokenizer was incorrectly instantiated with a model max length of 512 which will be corrected in Transformers v5.\n",
            "For now, this behavior is kept to avoid breaking backwards compatibility when padding/encoding with `truncation is True`.\n",
            "- Be aware that you SHOULD NOT rely on t5-base automatically truncating your input to 512 when padding/encoding.\n",
            "- If you want to encode/pad to sequences longer than 512 you can either instantiate this tokenizer with `model_max_length` or pass `max_length` when encoding/padding.\n",
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            "  FutureWarning,\n"
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              "|\u001b[1m                          review_body                          \u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m     review_headline     \u001b[0m|\n",
              "|----------------------------------------------------------------+--------------------------|\n",
              "|          summarize: Love this, excellent sun block!!           |        Five Stars        |\n",
              "|summarize: The great thing about this cream is that it doesn't  | Thank you Alba Bontanica!|\n",
              "| smell weird like all those chemical laden ones.  I get a nice  |                          |\n",
              "| healthy un-fake looking tan that isn't orange and it makes my  |                          |\n",
              "|                        skin soft too.                          |                          |\n",
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              "|----------------------------------------------------------------+--------------------------|\n",
              "|          summarize: Love this, excellent sun block!!           |        Five Stars        |\n",
              "|summarize: The great thing about this cream is that it doesn't  | Thank you Alba Bontanica!|\n",
              "| smell weird like all those chemical laden ones.  I get a nice  |                          |\n",
              "| healthy un-fake looking tan that isn't orange and it makes my  |                          |\n",
              "|                        skin soft too.                          |                          |\n",
              "+-------------------------------------------------------------------------------------------+\n",
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            "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33msnigdha0924\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n"
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              "+---------------------------------------------------------------------------+\n",
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              "|------+-------+------------------------------------------------------------|\n",
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              "|------+-------+------------------------------------------------------------|\n",
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              "+---------------------------------------------------------------------------+\n",
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              "|------+-------+------------------------------------------------------------|\n",
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              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "+---------------------------------------------------------------------------+\n",
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              "|------+-------+------------------------------------------------------------|\n",
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              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "+---------------------------------------------------------------------------+\n",
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              "|------+-------+------------------------------------------------------------|\n",
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              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "|------+-------+------------------------------------------------------------|\n",
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              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
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              "|------+-------+------------------------------------------------------------|\n",
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              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
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              "+---------------------------------------------------------------------------+\n",
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              "|------+-------+------------------------------------------------------------|\n",
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              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
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              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
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              "|------+-------+------------------------------------------------------------|\n",
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              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
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              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
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              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
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              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "+---------------------------------------------------------------------------+\n"
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              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
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              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
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              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
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              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
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              "+---------------------------------------------------------------------------+\n",
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              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
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            "text/html": [
              "Finishing last run (ID:3l00iwvc) before initializing another..."
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "VBox(children=(Label(value='0.001 MB of 0.001 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=1.0, max…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "bb02fd2a3a8746eba1ab5679bbdf24f6"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>Training Loss</td><td>█▄▄▄▂▄▁▄▂▂▂▃▄▂▃▄▂▂▃▃</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>Training Loss</td><td>2.65561</td></tr></table><br/></div></div>"
            ]
          },
          "metadata": {}
        },
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          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Synced <strong style=\"color:#cdcd00\">radiant-elevator-2</strong>: <a href=\"https://wandb.ai/snigdha0924/uncategorized/runs/3l00iwvc\" target=\"_blank\">https://wandb.ai/snigdha0924/uncategorized/runs/3l00iwvc</a><br/>Synced 4 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Find logs at: <code>./wandb/run-20220522_221239-3l00iwvc/logs</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Successfully finished last run (ID:3l00iwvc). Initializing new run:<br/>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Tracking run with wandb version 0.12.16"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Run data is saved locally in <code>/gdrive/MyDrive/wandb/run-20220522_221557-3j92dhir</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Syncing run <strong><a href=\"https://wandb.ai/snigdha0924/uncategorized/runs/3j92dhir\" target=\"_blank\">dandy-energy-3</a></strong> to <a href=\"https://wandb.ai/snigdha0924/uncategorized\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
            ]
          },
          "metadata": {}
        },
        {
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          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
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              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
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          "data": {
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
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          "data": {
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
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              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
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          "data": {
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
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          "data": {
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
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          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
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          "data": {
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
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          "data": {
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
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          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
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          "data": {
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
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          "data": {
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
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            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
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              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
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          "data": {
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Finishing last run (ID:3j92dhir) before initializing another..."
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "VBox(children=(Label(value='0.001 MB of 0.001 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=1.0, max…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "4ac467daa12c43e2843def58768e435f"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>Training Loss</td><td>▆▆▁█▃▆▅▂▄▄▃▂▂▄▂▁▅▃▁▂</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>Training Loss</td><td>0.72164</td></tr></table><br/></div></div>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Synced <strong style=\"color:#cdcd00\">dandy-energy-3</strong>: <a href=\"https://wandb.ai/snigdha0924/uncategorized/runs/3j92dhir\" target=\"_blank\">https://wandb.ai/snigdha0924/uncategorized/runs/3j92dhir</a><br/>Synced 4 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Find logs at: <code>./wandb/run-20220522_221557-3j92dhir/logs</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Successfully finished last run (ID:3j92dhir). Initializing new run:<br/>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Tracking run with wandb version 0.12.16"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Run data is saved locally in <code>/gdrive/MyDrive/wandb/run-20220522_221929-m0o32poo</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Syncing run <strong><a href=\"https://wandb.ai/snigdha0924/uncategorized/runs/m0o32poo\" target=\"_blank\">snowy-breeze-4</a></strong> to <a href=\"https://wandb.ai/snigdha0924/uncategorized\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
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          "data": {
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
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          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
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          "data": {
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              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
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          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  140  | tensor(0.8393, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  140  | tensor(0.8393, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  140  | tensor(0.8393, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  150  | tensor(1.3663, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  140  | tensor(0.8393, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  150  | tensor(1.3663, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  140  | tensor(0.8393, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  150  | tensor(1.3663, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  160  | tensor(0.4299, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  140  | tensor(0.8393, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  150  | tensor(1.3663, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  160  | tensor(0.4299, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  140  | tensor(0.8393, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  150  | tensor(1.3663, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  160  | tensor(0.4299, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  170  | tensor(0.9614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  140  | tensor(0.8393, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  150  | tensor(1.3663, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  160  | tensor(0.4299, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  170  | tensor(0.9614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
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              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  140  | tensor(0.8393, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  150  | tensor(1.3663, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  160  | tensor(0.4299, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  170  | tensor(0.9614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  180  | tensor(0.7019, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  140  | tensor(0.8393, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  150  | tensor(1.3663, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  160  | tensor(0.4299, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  170  | tensor(0.9614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  180  | tensor(0.7019, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[3m                               Training Status                               \u001b[0m\n",
              "+---------------------------------------------------------------------------+\n",
              "|\u001b[1mEpoch\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1mSteps\u001b[0m\u001b[1m \u001b[0m|\u001b[1m \u001b[0m\u001b[1m                           Loss                            \u001b[0m|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  140  | tensor(0.8393, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  150  | tensor(1.3663, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  160  | tensor(0.4299, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  170  | tensor(0.9614, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  180  | tensor(0.7019, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "|  2   |  190  | tensor(1.6533, device='cuda:0', grad_fn=<NllLossBackward0>)|\n",
              "+---------------------------------------------------------------------------+\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                               Training Status                               </span>\n",
              "+---------------------------------------------------------------------------+\n",
              "|<span style=\"font-weight: bold\">Epoch </span>|<span style=\"font-weight: bold\"> Steps </span>|<span style=\"font-weight: bold\">                            Loss                            </span>|\n",
              "|------+-------+------------------------------------------------------------|\n",
              "|  0   |   0   | tensor(6.9545, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  10   | tensor(3.0727, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  20   | tensor(3.5473, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  30   | tensor(3.3494, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  40   | tensor(1.5713, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  50   | tensor(2.7443, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  60   | tensor(0.3471, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  70   | tensor(3.1356, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  80   | tensor(1.0102, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  90   | tensor(1.4884, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  100  | tensor(1.1487, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  110  | tensor(2.0662, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  120  | tensor(2.9278, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  130  | tensor(0.9864, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  140  | tensor(1.7841, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  150  | tensor(3.1309, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  160  | tensor(1.4238, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  170  | tensor(1.1496, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  180  | tensor(1.9921, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  0   |  190  | tensor(2.6556, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |   0   | tensor(2.6863, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  10   | tensor(2.8146, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  20   | tensor(0.1080, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  30   | tensor(3.5588, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  40   | tensor(1.1581, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  50   | tensor(2.3447, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  60   | tensor(1.9585, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  70   | tensor(0.8284, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  80   | tensor(1.3856, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  90   | tensor(1.7681, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  100  | tensor(1.2898, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  110  | tensor(0.6740, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  120  | tensor(0.7849, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  130  | tensor(1.4947, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  140  | tensor(0.8144, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  150  | tensor(0.1905, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  160  | tensor(1.9436, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  170  | tensor(1.2157, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  180  | tensor(0.2861, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  1   |  190  | tensor(0.7216, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |   0   | tensor(1.7448, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  10   | tensor(2.0120, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  20   | tensor(1.3377, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  30   | tensor(0.4490, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  40   | tensor(1.6614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  50   | tensor(1.7783, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  60   | tensor(1.4264, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  70   | tensor(2.3036, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  80   | tensor(1.7087, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  90   | tensor(0.4967, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  100  | tensor(0.0529, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  110  | tensor(1.7482, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  120  | tensor(0.3767, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  130  | tensor(1.4212, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  140  | tensor(0.8393, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  150  | tensor(1.3663, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  160  | tensor(0.4299, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  170  | tensor(0.9614, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  180  | tensor(0.7019, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "|  2   |  190  | tensor(1.6533, device='cuda:0', grad_fn=&lt;NllLossBackward0&gt;)|\n",
              "+---------------------------------------------------------------------------+\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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              "\u001b[2;36m[22:23:26]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1m[\u001b[0mInitiating Validation\u001b[1m]\u001b[0m\u001b[33m...\u001b[0m                       \u001b[2m<ipython-input-6-5e83e2958eba>\u001b[0m\u001b[2m:\u001b[0m\u001b[2m87\u001b[0m\n",
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              "\u001b[2;36m[22:24:42]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1m[\u001b[0mValidation Completed.\u001b[1m]\u001b[0m                          \u001b[2m<ipython-input-6-5e83e2958eba>\u001b[0m\u001b[2m:\u001b[0m\u001b[2m95\u001b[0m\n",
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              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                                 </span>\n",
              "</pre>\n"
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          },
          "metadata": {}
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          "output_type": "display_data",
          "data": {
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              "\u001b[1m[\u001b[0mModel\u001b[1m]\u001b[0m Model saved @ outputs/model_files\n",
              "\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>Model<span style=\"font-weight: bold\">]</span> Model saved @ outputs/model_files\n",
              "\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m[\u001b[0mValidation\u001b[1m]\u001b[0m Generation on Validation data saved @ outputs/predictions.csv\n",
              "\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>Validation<span style=\"font-weight: bold\">]</span> Generation on Validation data saved @ outputs/predictions.csv\n",
              "\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import AutoTokenizer, AutoModelForSeq2SeqLM\n",
        "model = AutoModelForSeq2SeqLM.from_pretrained('t5-base')\n",
        "\n",
        "tokenizer = AutoTokenizer.from_pretrained('t5-base')"
      ],
      "metadata": {
        "id": "eH8duuxG42Wm",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 176,
          "referenced_widgets": [
            "fbd09495787c40a5b9f0fb0c1b9ff7eb",
            "23df664d083c438b83976dbc6bec3e47",
            "14928234e82b4131a85afad460627215",
            "efae2f72f2e64a9b8e538b61ef9fbdc3",
            "b04f1d75e9164819951a0d38d7abba97",
            "7954fca13d8c4ad3a3cb4eed799050ce",
            "f847322a09404451a39877b3face8c17",
            "02e04abe10534b4082000900bae34c80",
            "bd83502ae6cd46bf86f2d45b3fc38997",
            "238af984a5094e1d86fdf85913eac8fd",
            "edd2568ec539424597c0b62cfa190edc"
          ]
        },
        "outputId": "67702ef2-e303-4b74-cddd-0929c6987e90"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading:   0%|          | 0.00/1.32M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "fbd09495787c40a5b9f0fb0c1b9ff7eb"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/transformers/models/t5/tokenization_t5_fast.py:161: FutureWarning: This tokenizer was incorrectly instantiated with a model max length of 512 which will be corrected in Transformers v5.\n",
            "For now, this behavior is kept to avoid breaking backwards compatibility when padding/encoding with `truncation is True`.\n",
            "- Be aware that you SHOULD NOT rely on t5-base automatically truncating your input to 512 when padding/encoding.\n",
            "- If you want to encode/pad to sequences longer than 512 you can either instantiate this tokenizer with `model_max_length` or pass `max_length` when encoding/padding.\n",
            "- To avoid this warning, please instantiate this tokenizer with `model_max_length` set to your preferred value.\n",
            "  FutureWarning,\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install rouge_score\n",
        "from datasets import load_metric\n",
        "rouge_metric = load_metric(\"rouge\")\n",
        "records = []\n",
        "rouge_names = [\"rouge1\", \"rouge2\", \"rougeL\", \"rougeLsum\"]\n",
        "text=dataset['test']['review_body'][:2000]\n",
        "\n",
        "for review in text:\n",
        "  if review is not None:\n",
        "    tokens_input = tokenizer.encode(\"summarize: \"+review, return_tensors='pt', \n",
        "                                max_length=tokenizer.model_max_length, \n",
        "                                truncation=True)\n",
        "    summary_ids = model.generate(tokens_input, min_length=5,\n",
        "                             max_length=10,\n",
        "                             length_penalty=5, \n",
        "                             num_beams=2)\n",
        "\n",
        "    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)\n",
        "\n",
        "    rouge_metric.add(prediction=summary, reference=review)\n",
        "    score = rouge_metric.compute()\n",
        "    rouge_dict = dict((rn, score[rn].mid.fmeasure) for rn in rouge_names)\n",
        "    records.append(rouge_dict)"
      ],
      "metadata": {
        "id": "SHQkIY1Y2q3I",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 192,
          "referenced_widgets": [
            "4ddc1bf604f24452979e9d0f49220735",
            "6828ce7371b340958b4b29d61913c178",
            "7f64bd4cae064d1996bd6f0a767bb13f",
            "f7103f4bb6eb4045b7ca3892b9a1a538",
            "3d2506ce779f4877b9f7411dfa47ca4b",
            "abc86c5071b44de098783f80e9dfcaea",
            "528cd09b8d884799b77579ab33477372",
            "28c681bcc801460c8ac3aad2662713b4",
            "a8b6d50ac1d047b7a78b2c2cea494769",
            "7f3275e890604eda927d779ab3f992ee",
            "e8afc4501ae14569980922244fdc5618"
          ]
        },
        "outputId": "f5db5c79-8963-4cf2-ec87-647ebd7a7090"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting rouge_score\n",
            "  Downloading rouge_score-0.0.4-py2.py3-none-any.whl (22 kB)\n",
            "Requirement already satisfied: six>=1.14.0 in /usr/local/lib/python3.7/dist-packages (from rouge_score) (1.15.0)\n",
            "Requirement already satisfied: absl-py in /usr/local/lib/python3.7/dist-packages (from rouge_score) (1.0.0)\n",
            "Requirement already satisfied: nltk in /usr/local/lib/python3.7/dist-packages (from rouge_score) (3.2.5)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from rouge_score) (1.21.6)\n",
            "Installing collected packages: rouge-score\n",
            "Successfully installed rouge-score-0.0.4\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading builder script:   0%|          | 0.00/2.16k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "4ddc1bf604f24452979e9d0f49220735"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "rouge1=0\n",
        "rouge2=0\n",
        "rougeL=0\n",
        "rougeLsum=0\n",
        "for dict1 in records:\n",
        "  rouge1+=dict1['rouge1']\n",
        "  rouge2+=dict1['rouge2']\n",
        "  rougeL+=dict1['rougeL']\n",
        "  rougeLsum+=dict1['rougeLsum']\n",
        "\n",
        "#average rouge score of first 2000 rows of dataset  \n",
        "rouge1=rouge1/2000\n",
        "rouge2=rouge2/2000\n",
        "rougeL=rougeL/2000\n",
        "rougeLsum=rougeLsum/2000"
      ],
      "metadata": {
        "id": "id9LfgF76AG-"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "final_scores={'rouge1': rouge1, 'rouge2': rouge2, 'rougeL': rougeL, 'rougeLsum':rougeLsum}"
      ],
      "metadata": {
        "id": "Gk2zTY5OEl6j"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "final_scores"
      ],
      "metadata": {
        "id": "9M1C5YOqEolV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fd2cef0f-97cd-4fc6-df75-e0e971920b06"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'rouge1': 0.46896341113264345,\n",
              " 'rouge2': 0.388474233567936,\n",
              " 'rougeL': 0.4548153902899611,\n",
              " 'rougeLsum': 0.4548153902899611}"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "UjuASdBbA0Cn"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}