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cybersecurity_ner-v2
This model is a fine-tuned version of sudipadhikari/cybersecurity_ner-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1566
- Precision: 0.6414
- Recall: 0.6325
- F1: 0.6369
- Accuracy: 0.9666
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 176 | 0.1432 | 0.6236 | 0.6036 | 0.6135 | 0.9657 |
| No log | 2.0 | 352 | 0.1433 | 0.6655 | 0.6058 | 0.6342 | 0.9644 |
| 0.0341 | 3.0 | 528 | 0.1428 | 0.6124 | 0.6229 | 0.6176 | 0.9659 |
| 0.0341 | 4.0 | 704 | 0.1550 | 0.6345 | 0.6175 | 0.6259 | 0.9659 |
| 0.0341 | 5.0 | 880 | 0.1566 | 0.6414 | 0.6325 | 0.6369 | 0.9666 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
