GPT2-705M
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.4628
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: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 9.7135 | 0.57 | 1 | 9.7272 |
| 8.0222 | 1.71 | 3 | 9.3213 |
| 7.6063 | 2.86 | 5 | 8.5841 |
| 7.5596 | 4.0 | 7 | 7.9271 |
| 7.4194 | 4.57 | 8 | 8.0942 |
| 7.1644 | 5.71 | 10 | 7.5409 |
| 6.8531 | 6.86 | 12 | 7.3028 |
| 6.3614 | 8.0 | 14 | 9.3796 |
| 8.5129 | 8.57 | 15 | 7.6361 |
| 6.1325 | 9.71 | 17 | 6.7577 |
| 5.8526 | 10.86 | 19 | 6.5249 |
| 5.5941 | 12.0 | 21 | 6.2490 |
| 5.4307 | 12.57 | 22 | 6.2442 |
| 5.1381 | 13.71 | 24 | 5.9595 |
| 4.8705 | 14.86 | 26 | 5.8944 |
| 4.7083 | 16.0 | 28 | 5.7005 |
| 4.5355 | 16.57 | 29 | 5.7459 |
| 4.4187 | 17.71 | 31 | 5.5387 |
| 4.3123 | 18.86 | 33 | 5.4863 |
| 4.0269 | 20.0 | 35 | 5.3277 |
| 3.942 | 20.57 | 36 | 5.3274 |
| 3.784 | 21.71 | 38 | 5.3998 |
| 3.4991 | 22.86 | 40 | 5.4628 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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