bert-base-cased-5k-vul-hyp-exp-10ep
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3988
- Accuracy: 0.9167
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: 5e-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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.2981 | 1.0 | 530 | 0.3064 | 0.9216 |
0.2486 | 2.0 | 1060 | 0.2945 | 0.9314 |
0.3039 | 3.0 | 1590 | 0.2583 | 0.9289 |
0.2907 | 4.0 | 2120 | 0.3086 | 0.9240 |
0.2742 | 5.0 | 2650 | 0.2767 | 0.9363 |
0.2855 | 6.0 | 3180 | 0.3065 | 0.9265 |
0.245 | 7.0 | 3710 | 0.3074 | 0.9314 |
0.2565 | 8.0 | 4240 | 0.3487 | 0.9167 |
0.2299 | 9.0 | 4770 | 0.3449 | 0.9240 |
0.2233 | 10.0 | 5300 | 0.3988 | 0.9167 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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