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GPT2_Spirit-Anomaly
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0193
- Accuracy: 0.994
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 |
|---|---|---|---|---|
| 0.199 | 1.0 | 109 | 0.0795 | 0.9684 |
| 0.0528 | 1.99 | 218 | 0.0401 | 0.9850 |
| 0.0368 | 3.0 | 328 | 0.0305 | 0.9894 |
| 0.0298 | 3.99 | 437 | 0.0365 | 0.9870 |
| 0.0246 | 5.0 | 547 | 0.0185 | 0.9942 |
| 0.0233 | 6.0 | 656 | 0.0155 | 0.9946 |
| 0.0201 | 6.99 | 765 | 0.0161 | 0.9940 |
| 0.0189 | 8.0 | 875 | 0.0154 | 0.9944 |
| 0.0182 | 8.99 | 984 | 0.0150 | 0.9946 |
| 0.0196 | 9.96 | 1090 | 0.0135 | 0.9956 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
