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bert-base-chinese-finetuned-ner-food
This model is a fine-tuned version of bert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0039
- F1: 1.0
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 3.0829 | 1.0 | 3 | 1.6749 | 0.0 |
| 1.5535 | 2.0 | 6 | 1.0327 | 0.6354 |
| 1.0573 | 3.0 | 9 | 0.6295 | 0.7097 |
| 0.5854 | 4.0 | 12 | 0.3763 | 0.8271 |
| 0.4292 | 5.0 | 15 | 0.2165 | 0.9059 |
| 0.2235 | 6.0 | 18 | 0.1121 | 0.9836 |
| 0.1535 | 7.0 | 21 | 0.0597 | 0.9975 |
| 0.0846 | 8.0 | 24 | 0.0337 | 0.9975 |
| 0.0613 | 9.0 | 27 | 0.0214 | 1.0 |
| 0.0365 | 10.0 | 30 | 0.0144 | 1.0 |
| 0.0302 | 11.0 | 33 | 0.0103 | 1.0 |
| 0.0182 | 12.0 | 36 | 0.0078 | 1.0 |
| 0.0175 | 13.0 | 39 | 0.0064 | 1.0 |
| 0.0115 | 14.0 | 42 | 0.0055 | 1.0 |
| 0.0124 | 15.0 | 45 | 0.0049 | 1.0 |
| 0.0117 | 16.0 | 48 | 0.0045 | 1.0 |
| 0.0111 | 17.0 | 51 | 0.0042 | 1.0 |
| 0.0102 | 18.0 | 54 | 0.0041 | 1.0 |
| 0.0096 | 19.0 | 57 | 0.0040 | 1.0 |
| 0.0095 | 20.0 | 60 | 0.0039 | 1.0 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.12.0+cu102
- Datasets 1.18.4
- Tokenizers 0.12.1
