chinese-bert-wwm-ext-finetuned-ner
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0191
- Precision: 0.9469
- Recall: 0.9643
- F1: 0.9555
- Accuracy: 0.9952
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: 16
- eval_batch_size: 16
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|
| 0.0229 | 1.0 | 2319 | 0.0181 | 0.9380 | 0.9519 | 0.9449 | 0.9943 |
| 0.0102 | 2.0 | 4638 | 0.0189 | 0.9444 | 0.9642 | 0.9542 | 0.9948 |
| 0.0046 | 3.0 | 6957 | 0.0191 | 0.9469 | 0.9643 | 0.9555 | 0.9952 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
