Training in progress, epoch 1

.gitignore

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+checkpoint-*/

config.json

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+{
+  "activation": "relu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.05,
+  "cache_dir": null,
+  "dim": 768,
+  "dropout": 0.05,
+  "finetuning_task": "mnli",
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+  "id2label": {
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+    "1": "neutral",
+    "2": "contradiction"
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+  "label2id": {
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+    "entailment": 0,
+    "neutral": 1
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+  "max_position_embeddings": 512,
+  "model_type": "hybridbert",
+  "n_heads": 12,
+  "n_layers": 12,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "revision": "main",
+  "seq_classif_dropout": 0.1,
+  "sinusoidal_pos_embds": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.29.2",
+  "use_auth_token": null,
+  "vocab_size": 30522
+}

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pytorch_model.bin

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special_tokens_map.json

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+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
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tokenizer_config.json

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+{
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
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+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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