gpt2_small_EN_bpe_32768_parallel3-100_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9216
- Accuracy: 0.4506
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 |
|---|---|---|---|---|
| 3.5109 | 1.0 | 8069 | 3.4083 | 0.3977 |
| 3.2715 | 2.0 | 16138 | 3.1916 | 0.4187 |
| 3.1556 | 3.0 | 24207 | 3.0979 | 0.4281 |
| 3.0801 | 4.0 | 32276 | 3.0407 | 0.4356 |
| 3.0299 | 5.0 | 40345 | 3.0026 | 0.4400 |
| 2.9856 | 6.0 | 48414 | 2.9766 | 0.4427 |
| 2.9507 | 7.0 | 56483 | 2.9544 | 0.4460 |
| 2.9188 | 8.0 | 64552 | 2.9392 | 0.4483 |
| 2.8951 | 9.0 | 72621 | 2.9276 | 0.4498 |
| 2.8724 | 10.0 | 80690 | 2.9216 | 0.4506 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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