bert-finetuned-ner
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0626
- Precision: 0.9372
- Recall: 0.9519
- F1: 0.9445
- Accuracy: 0.9865
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 |
|---|---|---|---|---|---|---|---|
| 0.0735 | 1.0 | 1756 | 0.0664 | 0.9112 | 0.9376 | 0.9242 | 0.9818 |
| 0.0363 | 2.0 | 3512 | 0.0640 | 0.9358 | 0.9470 | 0.9414 | 0.9857 |
| 0.0213 | 3.0 | 5268 | 0.0626 | 0.9372 | 0.9519 | 0.9445 | 0.9865 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for JayBDev/bert-finetuned-ner
Base model
google-bert/bert-base-cased