ClimateQA / config.json
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{
"dataset_reader": {
"type": "ccqa",
"lazy": true,
"token_indexers": {
"bert": {
"type": "pretrained_transformer",
"model_name": "roberta-base"
}
},
"tokenizer": {
"type": "pretrained_transformer",
"add_special_tokens": false,
"model_name": "roberta-base"
}
},
"model": {
"type": "basic_classifier_modified",
"seq2vec_encoder": {
"type": "bert_pooler",
"override_weights_file": "PretrainedRoberta/checkpoint_best.pt",
"pretrained_model": "roberta-base",
"requires_grad": true
},
"text_field_embedder": {
"type": "basic",
"token_embedders": {
"bert": {
"type": "pretrained_transformer",
"last_layer_only": false,
"model_name": "roberta-base",
"override_weights_file": "PretrainedRoberta/checkpoint_best.pt"
}
}
}
},
"train_data_path": "SufficientCompanyData/train_df_balanced_1500_15000.tsv",
"validation_data_path": "SufficientCompanyData/val_df_balanced_750_7500.tsv",
"trainer": {
"checkpointer": {
"num_serialized_models_to_keep": 1
},
"cuda_device": 0,
"grad_norm": 1,
"num_epochs": 50,
"optimizer": {
"type": "huggingface_adamw",
"lr": 2e-06,
"weight_decay": 0.1
},
"validation_metric": "+accuracy"
},
"data_loader": {
"batch_size": 8
}
}