/
ranking_insurance.json
81 lines (81 loc) · 2.16 KB
/
ranking_insurance.json
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{
"dataset_reader": {
"name": "insurance_reader",
"data_path": "./insurance_data"
},
"dataset_iterator": {
"name": "ranking_iterator",
"seed": 243,
"len_vocab": 24981,
"sample_candidates_pool": false,
"sample_candidates_pool_valid": true,
"sample_candidates_pool_test": true,
"num_negative_samples": 5,
"num_ranking_samples_valid": 5,
"num_ranking_samples_test": 5
},
"chainer": {
"in": ["x"],
"in_y": ["y"],
"pipe": [
{
"in": ["x"],
"in_y": ["y"],
"out": ["y_predicted"],
"name": "ranking_model",
"device_num": 0,
"train_now": true,
"vocab_name": "insurance",
"vocabs_path": "insurance_data/insuranceQA-master/V1",
"embeddings": "random",
"embeddings_path": "insurance_embeddings/wiki.en.bin",
"embedding_dim": 300,
"use_matrix": false,
"seed": 243,
"max_sequence_length": 200,
"reccurent": "bilstm",
"max_pooling": true,
"shared_weights": true,
"hidden_dim": 300,
"learning_rate": 1e-3,
"distance": "cos_similarity",
"margin": 0.1,
"save_path": "insurance_ranking/model_weights.h5",
"load_path": "insurance_ranking/model_weights.h5",
"update_embeddings": true,
"interact_pred_num": 3
}
],
"out": ["y_predicted"]
},
"train": {
"epochs": 200,
"batch_size": 256,
"pytest_max_batches": 2,
"metrics": ["r@1", "rank_response", "loss"],
"validation_patience": 5,
"val_every_n_epochs": 10,
"log_every_n_batches": 10
},
"metadata": {
"requirements": [
"../dp_requirements/tf.txt",
"../dp_requirements/gensim.txt"
],
"labels": {
"telegram_utils": "RankingModel",
"server_utils": "Ranker"
},
"download": [
"http://files.deeppavlov.ai/deeppavlov_data/insurance_ranking_ds.tar.gz",
{
"url": "http://files.deeppavlov.ai/datasets/insuranceQA-master.zip",
"subdir": "insurance_data"
},
{
"url": "http://files.deeppavlov.ai/embeddings/wiki.en.bin",
"subdir": "insurance_embeddings"
}
]
}
}