| base_model: bert-base-chinese | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: bert-finetuned-ner | |
| 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-finetuned-ner | |
| This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1158 | |
| - Precision: 0.7635 | |
| - Recall: 0.7577 | |
| - F1: 0.7606 | |
| - Accuracy: 0.9626 | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 2e-05 | |
| - train_batch_size: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| | 0.1101 | 1.0 | 1875 | 0.1007 | 0.7357 | 0.7458 | 0.7407 | 0.9610 | | |
| | 0.0796 | 2.0 | 3750 | 0.1003 | 0.76 | 0.7530 | 0.7565 | 0.9627 | | |
| | 0.0538 | 3.0 | 5625 | 0.1158 | 0.7635 | 0.7577 | 0.7606 | 0.9626 | | |
| ### Framework versions | |
| - Transformers 4.40.2 | |
| - Pytorch 2.3.0 | |
| - Datasets 2.18.0 | |
| - Tokenizers 0.19.1 | |