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hparams.json
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hparams.json
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{
"py/object": "hparams.Hparams",
"model_hparams" : {
"py/object": "hparams.ModelHparams",
"rnn_cell_type": "lstm",
"rnn_size": 1024,
"use_bidirectional_encoder": true,
"encoder_num_layers": 4,
"decoder_num_layers": 4,
"encoder_embedding_size": 128,
"decoder_embedding_size": 128,
"encoder_embedding_trainable": true,
"decoder_embedding_trainable": true,
"share_embedding": true,
"attention_type": "normed_bahdanau",
"beam_width": 20,
"enable_sampling": false,
"optimizer": "sgd",
"max_gradient_norm": 5.0,
"gpu_dynamic_memory_growth": true
},
"training_hparams": {
"py/object": "hparams.TrainingHparams",
"min_question_words": 1,
"max_question_answer_words": 30,
"max_conversations": -1,
"conv_history_length": 6,
"normalize_words": false,
"input_vocab_threshold": 1,
"output_vocab_threshold": 1,
"input_vocab_import_normalized": true,
"output_vocab_import_normalized": true,
"input_vocab_import_mode": "Dataset",
"output_vocab_import_mode": "Dataset",
"validation_set_percent": 0.0,
"random_train_val_split": true,
"validation_metric": "loss",
"epochs": 500,
"early_stopping_epochs": 500,
"batch_size": 128,
"learning_rate": 2.0,
"learning_rate_decay": 0.9975,
"min_learning_rate": 0.1,
"dropout": 0.2,
"checkpoint_on_training": true,
"checkpoint_on_validation": false,
"log_summary": true,
"log_cleaned_dataset": true,
"log_training_data": true,
"stats_after_n_batches": 100,
"backup_on_training_loss": [3.0, 2.5, 2.0, 1.5, 1.0, 0.5]
},
"inference_hparams": {
"py/object": "hparams.InferenceHparams",
"beam_length_penalty_weight": 1.25,
"sampling_temperature": 0.5,
"max_answer_words": 100,
"conv_history_length": 20,
"normalize_words": false,
"log_summary": true,
"log_chat": true
}
}