GPT2_BGL-Anomaly_Baseline
This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2556
- Accuracy: 0.9314
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 320
- 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 |
|---|---|---|---|---|
| 1.2781 | 1.0 | 109 | 1.0676 | 0.7345 |
| 0.7136 | 1.99 | 218 | 0.4827 | 0.8090 |
| 0.4157 | 3.0 | 328 | 0.2764 | 0.9246 |
| 0.3372 | 3.99 | 437 | 0.2637 | 0.9294 |
| 0.3147 | 5.0 | 547 | 0.2616 | 0.9308 |
| 0.3112 | 6.0 | 656 | 0.2600 | 0.9304 |
| 0.3059 | 6.99 | 765 | 0.2581 | 0.9306 |
| 0.297 | 8.0 | 875 | 0.2570 | 0.9308 |
| 0.2976 | 8.99 | 984 | 0.2562 | 0.9312 |
| 0.2972 | 9.96 | 1090 | 0.2558 | 0.9312 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3