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GPT2_Spirit-Anomaly_Baseline
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3795
- Accuracy: 0.8071
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 |
|---|---|---|---|---|
| 0.9459 | 1.0 | 109 | 0.6442 | 0.6759 |
| 0.7795 | 1.99 | 218 | 0.5496 | 0.7339 |
| 0.6704 | 3.0 | 328 | 0.4965 | 0.7664 |
| 0.6 | 3.99 | 437 | 0.4615 | 0.7710 |
| 0.5469 | 5.0 | 547 | 0.4343 | 0.7794 |
| 0.5148 | 6.0 | 656 | 0.4156 | 0.7844 |
| 0.4861 | 6.99 | 765 | 0.4013 | 0.7914 |
| 0.4681 | 8.0 | 875 | 0.3929 | 0.7970 |
| 0.4554 | 8.99 | 984 | 0.3873 | 0.8004 |
| 0.4504 | 9.96 | 1090 | 0.3860 | 0.8018 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
