gpt2_small_RU_unigram_49152_parallel10_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.8834
- Accuracy: 0.3801
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 |
|---|---|---|---|---|
| 6.258 | 1.0 | 1513 | 4.8358 | 0.3197 |
| 4.5459 | 2.0 | 3026 | 4.4002 | 0.3434 |
| 4.3502 | 3.0 | 4539 | 4.2115 | 0.3556 |
| 4.1438 | 4.0 | 6052 | 4.0998 | 0.3629 |
| 4.0583 | 5.0 | 7565 | 4.0244 | 0.3684 |
| 3.9573 | 6.0 | 9078 | 3.9694 | 0.3728 |
| 3.9044 | 7.0 | 10591 | 3.9343 | 0.3757 |
| 3.8477 | 8.0 | 12104 | 3.9075 | 0.3783 |
| 3.8147 | 9.0 | 13617 | 3.8904 | 0.3797 |
| 3.7834 | 10.0 | 15130 | 3.8834 | 0.3801 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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