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Error running the configuring parameters cell #14
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Make sure you successfully downloaded the language model ( |
Thanks for your feedback. Moreover, how I can construct the files train.csv, validation.csv, test.csv? |
Apologies if I was clear, but my main question is how to retrieve the train, validation and test data and put it in those files? |
Take a look at this #8 |
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When I did a "batch response: This repository is over its data quota. Account responsible for LFS bandwidth should purchase more data packs to restore access. This is probably related to this issue. |
You could manually download https://github.com/ProsusAI/finBERT/raw/master/models/language_model/finbertTRC2/pytorch_model.bin from the browser, that's what I did |
Did you try manually downloading the file from the browser from https://github.com/ProsusAI/finBERT/raw/master/models/language_model/finbertTRC2/pytorch_model.bin? It worked for me and the downloaded file is approximately 400MB |
Can you share your local copy of the model file? This method no longer works due to GitHub bandwidth restrictions. I can download the file but it's only 134 bytes. Thank you |
@davidifshk you can also use my link if you want ^ |
@bernardmizzi Thank you. This is going to benefit more people with the same issue. |
No problem, glad I could help |
Sorry to ask again, but could you please also share the model under classifier_model/finbert-sentiment. I believe that could not be downloaded as well. Really appreciate your help! |
That model is created when trained on certain text, you'll have to run the notebook finBERT/notebooks/finbert_training.ipynb as mine is trained on certain text. If you want i'll give you mine but it is trained on reddit news headlines and obviously it reported very low accuracy. |
That's okay. Thank you very much! |
Should you need help with running the notebook just send me a message as I got it up and running. |
It works! Thank you very much! I'm going to run the training with the dataset from FinancialPhraseBank first. |
@davidifshk I wan't able to run the model on the PhaseBank Dataset as I was getting encoding errors on both windows and ubuntu systems. Thus I opted for another dataset. |
@davidifshk would it be a problem to provide me the code you used to open and format the PhraseBank dataset as I was getting encoding errors? |
Im trying to use finbert for classification of new articles into several different categories in the banking domain . Which model should i use for classification . |
You have to run the notebook FinBERT/notebooks/finbert_training.ipynb which will train the language model, then it will create a new classification model, which then, will continuing running the notebook, will use it for classification |
@bernardmizzi Your link to model from google drive has expired, can you re-upload it please? When trying to download model from repository I get error:
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Thanks a lot @bernardmizzi ! Could you upload also the sentiment model weights? |
The model is already pre-trained and can be used. I think the model weights are embedded within the model. To run finbert, all you need s the pythorch model bin file and its config. |
You'll have to run the notebook finbert_training.ipynb since the model you are asking for is fine-tuned (trained) on a certain dataset, and that depends on which dataset you want |
I actually need it fine-tuned on financial news, so if you can upload the fine-tuned version of the sentiment-analysis one, I'd be glad! Thank you anyway. |
@bernardmizzi you're right, didn't went carefully enough through the read me to notice that. Thanks for your help! |
Hi, how to settle this issue? |
Good morning,
I am running the configuring parameters cell and I am getting the below error:
UnpicklingError Traceback (most recent call last)
in
5 pass
6
----> 7 bertmodel = BertForSequenceClassification.from_pretrained(lm_path,cache_dir=None, num_labels=3)
8
9
~/anaconda3/envs/finbert/lib/python3.7/site-packages/pytorch_pretrained_bert/modeling.py in from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs)
601 if state_dict is None and not from_tf:
602 weights_path = os.path.join(serialization_dir, WEIGHTS_NAME)
--> 603 state_dict = torch.load(weights_path, map_location='cpu')
604 if tempdir:
605 # Clean up temp dir
~/anaconda3/envs/finbert/lib/python3.7/site-packages/torch/serialization.py in load(f, map_location, pickle_module, **pickle_load_args)
385 f = f.open('rb')
386 try:
--> 387 return _load(f, map_location, pickle_module, **pickle_load_args)
388 finally:
389 if new_fd:
~/anaconda3/envs/finbert/lib/python3.7/site-packages/torch/serialization.py in _load(f, map_location, pickle_module, **pickle_load_args)
562 f.seek(0)
563
--> 564 magic_number = pickle_module.load(f, **pickle_load_args)
565 if magic_number != MAGIC_NUMBER:
566 raise RuntimeError("Invalid magic number; corrupt file?")
UnpicklingError: invalid load key, 'v'.
Moreover, can you kindly explain how I can construct the files train.csv, validation.csv, test.csv?
Regards,
Bernard
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