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bert-finetuned-ner
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0113
- Precision: 0.9571
- Recall: 0.8933
- F1: 0.9241
- Accuracy: 0.9935
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 25 | 0.0296 | 0.9286 | 0.8667 | 0.8966 | 0.9870 |
| No log | 2.0 | 50 | 0.0087 | 0.9722 | 0.9333 | 0.9524 | 0.9961 |
| No log | 3.0 | 75 | 0.0113 | 0.9571 | 0.8933 | 0.9241 | 0.9935 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
