bert-small-finetuned-xglue-ner-longer20
This model is a fine-tuned version of muhtasham/bert-small-finetuned-xglue-ner-longer10 on the wnut_17 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5839
- Precision: 0.5783
- Recall: 0.4330
- F1: 0.4952
- Accuracy: 0.9261
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 425 | 0.4882 | 0.5 | 0.4510 | 0.4742 | 0.9228 |
| 0.013 | 2.0 | 850 | 0.5039 | 0.5130 | 0.4246 | 0.4647 | 0.9242 |
| 0.0124 | 3.0 | 1275 | 0.5331 | 0.5506 | 0.4426 | 0.4907 | 0.9256 |
| 0.0159 | 4.0 | 1700 | 0.5403 | 0.5488 | 0.4234 | 0.4781 | 0.9249 |
| 0.0132 | 5.0 | 2125 | 0.5459 | 0.5714 | 0.4211 | 0.4848 | 0.9255 |
| 0.0117 | 6.0 | 2550 | 0.5522 | 0.5637 | 0.4342 | 0.4905 | 0.9253 |
| 0.0117 | 7.0 | 2975 | 0.5712 | 0.5778 | 0.4354 | 0.4966 | 0.9257 |
| 0.007 | 8.0 | 3400 | 0.5860 | 0.5828 | 0.4378 | 0.5 | 0.9259 |
| 0.0066 | 9.0 | 3825 | 0.5745 | 0.5703 | 0.4462 | 0.5007 | 0.9259 |
| 0.0049 | 10.0 | 4250 | 0.5839 | 0.5783 | 0.4330 | 0.4952 | 0.9261 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1