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bert-base-chinese-finetuned-ner-food_requirement
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: 0.0046
- 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 |
|---|---|---|---|---|
| 3.169 | 1.0 | 3 | 1.7537 | 0.0 |
| 1.598 | 2.0 | 6 | 1.0914 | 0.5169 |
| 1.1569 | 3.0 | 9 | 0.6879 | 0.7057 |
| 0.6669 | 4.0 | 12 | 0.4194 | 0.8607 |
| 0.485 | 5.0 | 15 | 0.2528 | 0.9333 |
| 0.2807 | 6.0 | 18 | 0.1476 | 0.9836 |
| 0.2015 | 7.0 | 21 | 0.0834 | 0.9873 |
| 0.1145 | 8.0 | 24 | 0.0484 | 0.9924 |
| 0.0809 | 9.0 | 27 | 0.0283 | 1.0 |
| 0.0495 | 10.0 | 30 | 0.0180 | 1.0 |
| 0.0377 | 11.0 | 33 | 0.0126 | 1.0 |
| 0.0219 | 12.0 | 36 | 0.0095 | 1.0 |
| 0.0216 | 13.0 | 39 | 0.0076 | 1.0 |
| 0.015 | 14.0 | 42 | 0.0065 | 1.0 |
| 0.0176 | 15.0 | 45 | 0.0059 | 1.0 |
| 0.0161 | 16.0 | 48 | 0.0053 | 1.0 |
| 0.0133 | 17.0 | 51 | 0.0050 | 1.0 |
| 0.0119 | 18.0 | 54 | 0.0048 | 1.0 |
| 0.0116 | 19.0 | 57 | 0.0047 | 1.0 |
| 0.0126 | 20.0 | 60 | 0.0046 | 1.0 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.12.0+cu102
- Datasets 1.18.4
- Tokenizers 0.12.1
