gpt2_small_RU_superbpe_81920_parallel10_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.4826
- Accuracy: 0.2490
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: 64
- eval_batch_size: 64
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 128
- total_eval_batch_size: 128
- 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 |
|---|---|---|---|---|
| 8.1818 | 1.0 | 1108 | 7.1922 | 0.1818 |
| 6.9358 | 2.0 | 2216 | 6.4720 | 0.2028 |
| 6.399 | 3.0 | 3324 | 6.0941 | 0.2168 |
| 6.083 | 4.0 | 4432 | 5.8770 | 0.2265 |
| 5.8741 | 5.0 | 5540 | 5.7324 | 0.2338 |
| 5.7277 | 6.0 | 6648 | 5.6334 | 0.2396 |
| 5.6161 | 7.0 | 7756 | 5.5662 | 0.2433 |
| 5.5316 | 8.0 | 8864 | 5.5215 | 0.2463 |
| 5.4675 | 9.0 | 9972 | 5.4928 | 0.2481 |
| 5.3844 | 10.0 | 11080 | 5.4826 | 0.2490 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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