GPT2-705M
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3542
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: 0.00025
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.7388 | 1.0 | 3 | 6.6745 |
| 7.7712 | 2.0 | 6 | 6.9355 |
| 5.7851 | 3.0 | 9 | 6.0090 |
| 4.8315 | 4.0 | 12 | 5.7252 |
| 4.7133 | 5.0 | 15 | 5.2462 |
| 4.7276 | 6.0 | 18 | 4.9371 |
| 4.2828 | 7.0 | 21 | 4.8806 |
| 4.3069 | 8.0 | 24 | 4.4319 |
| 4.1875 | 9.0 | 27 | 4.2952 |
| 3.8318 | 10.0 | 30 | 4.1134 |
| 3.6746 | 11.0 | 33 | 3.9505 |
| 3.5241 | 12.0 | 36 | 3.7828 |
| 3.2439 | 13.0 | 39 | 3.7290 |
| 3.2954 | 14.0 | 42 | 3.5655 |
| 2.9475 | 15.0 | 45 | 3.4805 |
| 2.9343 | 16.0 | 48 | 3.5263 |
| 2.8517 | 17.0 | 51 | 3.4318 |
| 2.5458 | 18.0 | 54 | 3.3942 |
| 2.4846 | 19.0 | 57 | 3.3714 |
| 2.5766 | 20.0 | 60 | 3.3542 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Downloads last month
- 1