bert-base-NER
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0642
- Precision: 1.0
- Recall: 0.9711
- F1: 0.9853
- Accuracy: 0.9790
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|
| No log | 1.0 | 8 | 0.0885 | 1.0 | 0.9480 | 0.9733 | 0.9622 |
| No log | 2.0 | 16 | 0.0642 | 1.0 | 0.9711 | 0.9853 | 0.9790 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
