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  1. README.md +55 -0
  2. all_results.json +14 -0
  3. config.json +40 -0
  4. eval_results.json +9 -0
  5. pytorch_model.bin +3 -0
  6. runs/Dec04_12-08-27_PC-202211211407/1670126920.1115255/events.out.tfevents.1670126920.PC-202211211407.10264.1 +3 -0
  7. runs/Dec04_12-08-27_PC-202211211407/events.out.tfevents.1670126920.PC-202211211407.10264.0 +3 -0
  8. runs/Dec04_12-14-19_PC-202211211407/1670127270.830989/events.out.tfevents.1670127270.PC-202211211407.3532.1 +3 -0
  9. runs/Dec04_12-14-19_PC-202211211407/events.out.tfevents.1670127270.PC-202211211407.3532.0 +3 -0
  10. runs/Dec04_12-23-03_PC-202211211407/1670127795.0052035/events.out.tfevents.1670127795.PC-202211211407.4408.1 +3 -0
  11. runs/Dec04_12-23-03_PC-202211211407/events.out.tfevents.1670127794.PC-202211211407.4408.0 +3 -0
  12. runs/Dec04_12-35-35_PC-202211211407/1670128547.0779657/events.out.tfevents.1670128547.PC-202211211407.6468.1 +3 -0
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  14. runs/Dec04_12-43-14_PC-202211211407/1670129005.8312/events.out.tfevents.1670129005.PC-202211211407.12248.1 +3 -0
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  16. runs/Dec04_12-55-19_PC-202211211407/1670129735.5714748/events.out.tfevents.1670129735.PC-202211211407.4668.1 +3 -0
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  18. runs/Dec04_12-55-19_PC-202211211407/events.out.tfevents.1670132477.PC-202211211407.4668.2 +3 -0
  19. special_tokens_map.json +7 -0
  20. tokenizer.json +0 -0
  21. tokenizer_config.json +14 -0
  22. train_results.json +8 -0
  23. trainer_state.json +25 -0
  24. training_args.bin +3 -0
  25. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: bert_cn_finetuning_test
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # bert_cn_finetuning_test
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+
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+ This model is a fine-tuned version of [.\bert-base-chinese\](https://huggingface.co/.\bert-base-chinese\) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3328
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+ - Accuracy: 0.8850
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 1.0
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.25.0
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+ - Pytorch 1.12.0+cpu
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+ - Datasets 2.7.1
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+ - Tokenizers 0.11.6
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+ "eval_samples_per_second": 4.216,
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+ "eval_steps_per_second": 0.527,
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+ "train_loss": 0.37803538554423566,
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+ "train_samples": 2960,
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+ "train_samples_per_second": 1.189,
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+ "train_steps_per_second": 0.149
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+ }
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+ {
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+ "_name_or_path": ".\\bert-base-chinese\\",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "directionality": "bidi",
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.25.0",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ }
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