gpt2_small_FI_superbpe_8192_parallel10_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.9106
- Accuracy: 0.3326
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: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 6.6767 | 1.0 | 1429 | 5.1691 | 0.2138 |
| 5.2109 | 2.0 | 2858 | 4.5450 | 0.2634 |
| 4.4688 | 3.0 | 4287 | 4.2958 | 0.2882 |
| 4.3088 | 4.0 | 5716 | 4.1568 | 0.3031 |
| 4.1189 | 5.0 | 7145 | 4.0696 | 0.3128 |
| 4.0477 | 6.0 | 8574 | 4.0116 | 0.3192 |
| 3.9598 | 7.0 | 10003 | 3.9688 | 0.3246 |
| 3.912 | 8.0 | 11432 | 3.9395 | 0.3282 |
| 3.8861 | 9.0 | 12861 | 3.9198 | 0.3313 |
| 3.8401 | 10.0 | 14290 | 3.9106 | 0.3326 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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