Add model config

custom_config.json

@@ -0,0 +1,128 @@
+{
+  "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"
+  }
+}