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  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ base_model: bert-base-chinese
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: bert-base-chinese-ner
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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-base-chinese-ner
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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: 0.0411
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+ - Precision: 0.9361
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+ - Recall: 0.9237
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+ - F1: 0.9299
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+ - Accuracy: 0.9919
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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: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 16
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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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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0839 | 1.0 | 5796 | 0.0400 | 0.8999 | 0.8866 | 0.8932 | 0.9891 |
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+ | 0.0266 | 2.0 | 11592 | 0.0378 | 0.9227 | 0.9195 | 0.9211 | 0.9910 |
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+ | 0.0124 | 3.0 | 17388 | 0.0411 | 0.9361 | 0.9237 | 0.9299 | 0.9919 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.2
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+ - Pytorch 2.2.2+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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