Training in progress, epoch 1

config.json

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+{
+  "_name_or_path": "google-bert/bert-base-uncased",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "B-Ceramics_Glasses",
+    "1": "B-Composites_Layers_Coverings",
+    "2": "B-Copolymers_Blends",
+    "3": "B-Metals_Alloys",
+    "4": "B-Natural_Polymer",
+    "5": "B-Synthetic_Polymer",
+    "6": "B-Trade_Name_Biomat",
+    "7": "B-chemical_Material",
+    "8": "I-Ceramics_Glasses",
+    "9": "I-Composites_Layers_Coverings",
+    "10": "I-Copolymers_Blends",
+    "11": "I-Metals_Alloys",
+    "12": "I-Natural_Polymer",
+    "13": "I-Synthetic_Polymer",
+    "14": "I-Trade_Name_Biomat",
+    "15": "I-chemical_Material",
+    "16": "O"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-Ceramics_Glasses": 0,
+    "B-Composites_Layers_Coverings": 1,
+    "B-Copolymers_Blends": 2,
+    "B-Metals_Alloys": 3,
+    "B-Natural_Polymer": 4,
+    "B-Synthetic_Polymer": 5,
+    "B-Trade_Name_Biomat": 6,
+    "B-chemical_Material": 7,
+    "I-Ceramics_Glasses": 8,
+    "I-Composites_Layers_Coverings": 9,
+    "I-Copolymers_Blends": 10,
+    "I-Metals_Alloys": 11,
+    "I-Natural_Polymer": 12,
+    "I-Synthetic_Polymer": 13,
+    "I-Trade_Name_Biomat": 14,
+    "I-chemical_Material": 15,
+    "O": 16
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.42.4",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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+size 435642228

runs/Sep02_22-21-10_e8f1885030ef/events.out.tfevents.1725315672.e8f1885030ef.603.0

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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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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "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]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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