End of training

config.json

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+{
+  "_name_or_path": "microsoft/MiniLM-L12-H384-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "id2label": {
+    "0": "Society & Culture",
+    "1": "Science & Mathematics",
+    "2": "Health",
+    "3": "Education & Reference",
+    "4": "Computers & Internet",
+    "5": "Sports",
+    "6": "Business & Finance",
+    "7": "Entertainment & Music",
+    "8": "Family & Relationships",
+    "9": "Politics & Government"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "label2id": {
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+    "Computers & Internet": 4,
+    "Education & Reference": 3,
+    "Entertainment & Music": 7,
+    "Family & Relationships": 8,
+    "Health": 2,
+    "Politics & Government": 9,
+    "Science & Mathematics": 1,
+    "Society & Culture": 0,
+    "Sports": 5
+  },
+  "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",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.31.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

pytorch_model.bin

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special_tokens_map.json

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+  "sep_token": "[SEP]",
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tokenizer_config.json

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+  "do_lower_case": true,
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+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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