gpt2_small_RU_unigram_8192_parallel10_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.2216
- Accuracy: 0.4080
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 |
|---|---|---|---|---|
| 5.5524 | 1.0 | 1831 | 4.0853 | 0.3139 |
| 3.9442 | 2.0 | 3662 | 3.6704 | 0.3547 |
| 3.6249 | 3.0 | 5493 | 3.5017 | 0.3725 |
| 3.4711 | 4.0 | 7324 | 3.4063 | 0.3853 |
| 3.3731 | 5.0 | 9155 | 3.3419 | 0.3924 |
| 3.3219 | 6.0 | 10986 | 3.2977 | 0.3984 |
| 3.2583 | 7.0 | 12817 | 3.2679 | 0.4023 |
| 3.2144 | 8.0 | 14648 | 3.2443 | 0.4050 |
| 3.1801 | 9.0 | 16479 | 3.2291 | 0.4073 |
| 3.1546 | 10.0 | 18310 | 3.2216 | 0.4080 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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