| --- |
| library_name: transformers |
| base_model: google-bert/bert-base-chinese |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: bert-ner-msra |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # bert-ner-msra |
|
|
| This model is a fine-tuned version of [google-bert/bert-base-chinese](https://huggingface.co/google-bert/bert-base-chinese) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - eval_loss: 0.0413 |
| - eval_precision: 0.9481 |
| - eval_recall: 0.9507 |
| - eval_f1: 0.9494 |
| - eval_accuracy: 0.9939 |
| - eval_runtime: 10.3612 |
| - eval_samples_per_second: 421.283 |
| - eval_steps_per_second: 13.222 |
| - epoch: 9.0 |
| - step: 13041 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
|
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| More information needed |
|
|
| ## Training and evaluation data |
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|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
|
|
| ### Framework versions |
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|
| - Transformers 4.46.1 |
| - Pytorch 2.4.1+cu124 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.1 |
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|
