| { | |
| "dataset_reader": { | |
| "class_name": "basic_classification_reader", | |
| "x": "text", | |
| "y": "sentiment", | |
| "data_path": "/train/", | |
| "train": "train.csv", | |
| "valid": "valid.csv" | |
| }, | |
| "dataset_iterator": { | |
| "class_name": "basic_classification_iterator", | |
| "seed": 42 | |
| }, | |
| "chainer": { | |
| "in": [ | |
| "x" | |
| ], | |
| "in_y": [ | |
| "y" | |
| ], | |
| "pipe": [ | |
| { | |
| "id": "classes_vocab", | |
| "class_name": "simple_vocab", | |
| "fit_on": [ | |
| "y" | |
| ], | |
| "save_path": "custom_bert/classes.dict", | |
| "load_path": "custom_bert/classes.dict", | |
| "in": "y", | |
| "out": "y_ids" | |
| }, | |
| { | |
| "class_name": "transformers_bert_preprocessor", | |
| "vocab_file": "vocab.txt", | |
| "do_lower_case": false, | |
| "max_seq_length": 512, | |
| "in": ["x"], | |
| "out": ["tokens", "subword_tokens", "subword_tok_ids", "startofword_markers", "attention_mask"] | |
| }, | |
| { | |
| "class_name": "transformers_bert_embedder", | |
| "id": "my_embedder", | |
| "bert_config_path": "config.json", | |
| "truncate": false, | |
| "load_path": "custom_bert", | |
| "in": ["subword_tok_ids", "startofword_markers", "attention_mask"], | |
| "out": ["word_emb", "subword_emb", "max_emb", "mean_emb", "pooler_output"] | |
| }, | |
| { | |
| "in": "y_ids", | |
| "out": "y_onehot", | |
| "class_name": "one_hotter", | |
| "depth": "#classes_vocab.len", | |
| "single_vector": true | |
| }, | |
| { | |
| "in": [ | |
| "word_emb" | |
| ], | |
| "in_y": [ | |
| "y_onehot" | |
| ], | |
| "out": [ | |
| "y_pred_probas" | |
| ], | |
| "main": true, | |
| "class_name": "keras_classification_model", | |
| "save_path": "custom_bert/model", | |
| "load_path": "custom_bert/model", | |
| "embedding_size": "#my_embedder.dim", | |
| "n_classes": "#classes_vocab.len", | |
| "kernel_sizes_cnn": [ | |
| 3, | |
| 5, | |
| 7 | |
| ], | |
| "filters_cnn": 512, | |
| "optimizer": "Adam", | |
| "learning_rate": 0.01, | |
| "learning_rate_decay": 0.1, | |
| "loss": "categorical_crossentropy", | |
| "last_layer_activation": "softmax", | |
| "coef_reg_cnn": 1e-3, | |
| "coef_reg_den": 1e-2, | |
| "dropout_rate": 0.5, | |
| "dense_size": 100, | |
| "model_name": "cnn_model" | |
| }, | |
| { | |
| "in": "y_pred_probas", | |
| "out": "y_pred_ids", | |
| "class_name": "proba2labels", | |
| "max_proba": true | |
| }, | |
| { | |
| "in": "y_pred_ids", | |
| "out": "y_pred_labels", | |
| "ref": "classes_vocab" | |
| } | |
| ], | |
| "out": [ | |
| "y_pred_labels" | |
| ] | |
| }, | |
| "train": { | |
| "epochs": 3, | |
| "batch_size": 16, | |
| "metrics": [ | |
| "accuracy", | |
| "f1_macro", | |
| "f1_weighted", | |
| { | |
| "name": "roc_auc", | |
| "inputs": ["y_onehot", "y_pred_probas"] | |
| } | |
| ], | |
| "validation_patience": 1, | |
| "val_every_n_epochs": 1, | |
| "log_every_n_epochs": 1, | |
| "show_examples": false, | |
| "evaluation_targets": [ | |
| "train", | |
| "valid" | |
| ], | |
| "class_name": "nn_trainer" | |
| } | |
| } | |