ner-bio-annotated-7
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3098
- Precision: 0.6877
- Recall: 0.7570
- F1: 0.7207
- Accuracy: 0.8997
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
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 67 | 0.5051 | 0.4822 | 0.6199 | 0.5425 | 0.8298 |
| No log | 2.0 | 134 | 0.3376 | 0.6670 | 0.7173 | 0.6913 | 0.8889 |
| No log | 3.0 | 201 | 0.3098 | 0.6877 | 0.7570 | 0.7207 | 0.8997 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0+cpu
- Datasets 2.1.0
- Tokenizers 0.13.3