Training in progress, epoch 1

.gitignore

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+checkpoint-*/

config.json

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+{
+  "_name_or_path": "distilbert-base-uncased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForTokenClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "O",
+    "1": "B-FOOD",
+    "2": "I-FOOD",
+    "3": "B-QUANTITY",
+    "4": "I-QUANTITY",
+    "5": "B-UNIT",
+    "6": "I-UNIT",
+    "7": "B-PROCESS",
+    "8": "I-PROCESS",
+    "9": "B-PHYSICAL_QUALITY",
+    "10": "I-PHYSICAL_QUALITY",
+    "11": "B-COLOR",
+    "12": "I-COLOR",
+    "13": "B-TASTE",
+    "14": "I-TASTE",
+    "15": "B-PURPOSE",
+    "16": "I-PURPOSE",
+    "17": "B-PART",
+    "18": "I-PART"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
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+    "B-FOOD": 1,
+    "B-PART": 17,
+    "B-PHYSICAL_QUALITY": 9,
+    "B-PROCESS": 7,
+    "B-PURPOSE": 15,
+    "B-QUANTITY": 3,
+    "B-TASTE": 13,
+    "B-UNIT": 5,
+    "I-COLOR": 12,
+    "I-FOOD": 2,
+    "I-PART": 18,
+    "I-PHYSICAL_QUALITY": 10,
+    "I-PROCESS": 8,
+    "I-PURPOSE": 16,
+    "I-QUANTITY": 4,
+    "I-TASTE": 14,
+    "I-UNIT": 6,
+    "O": 0
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.26.0",
+  "vocab_size": 30522
+}

pytorch_model.bin

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special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "name_or_path": "distilbert-base-uncased",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "special_tokens_map_file": null,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "DistilBertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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