gpt2_small_EN_unigram_32768_parallel10_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.4314
- Accuracy: 0.3923
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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- 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 |
|---|---|---|---|---|
| 3.9999 | 1.0 | 6622 | 3.8910 | 0.3536 |
| 3.7531 | 2.0 | 13244 | 3.7011 | 0.3664 |
| 3.6353 | 3.0 | 19866 | 3.6027 | 0.3747 |
| 3.5358 | 4.0 | 26488 | 3.5417 | 0.3798 |
| 3.459 | 5.0 | 33110 | 3.5014 | 0.3837 |
| 3.3999 | 6.0 | 39732 | 3.4717 | 0.3869 |
| 3.3415 | 7.0 | 46354 | 3.4540 | 0.3884 |
| 3.2903 | 8.0 | 52976 | 3.4421 | 0.3905 |
| 3.2483 | 9.0 | 59598 | 3.4340 | 0.3918 |
| 3.2097 | 10.0 | 66220 | 3.4314 | 0.3923 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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