rus_gpt2_continued
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.5007
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: 0.005
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.1129 | 0.1698 | 1000 | 3.0504 |
3.0676 | 0.3396 | 2000 | 3.0015 |
3.0157 | 0.5094 | 3000 | 2.9528 |
2.9646 | 0.6792 | 4000 | 2.9015 |
2.9108 | 0.8490 | 5000 | 2.8427 |
2.8472 | 1.0188 | 6000 | 2.7835 |
2.7629 | 1.1886 | 7000 | 2.7155 |
2.6931 | 1.3583 | 8000 | 2.6456 |
2.6264 | 1.5281 | 9000 | 2.5798 |
2.5615 | 1.6979 | 10000 | 2.5268 |
2.5206 | 1.8677 | 11000 | 2.5007 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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