gpt2_small_EN_unigram_49152_parallel10_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.5684
- Accuracy: 0.3855
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 |
|---|---|---|---|---|
| 5.8213 | 1.0 | 1628 | 4.1949 | 0.3398 |
| 4.0577 | 2.0 | 3256 | 3.9153 | 0.3575 |
| 3.9228 | 3.0 | 4884 | 3.7901 | 0.3662 |
| 3.769 | 4.0 | 6512 | 3.7143 | 0.3726 |
| 3.6769 | 5.0 | 8140 | 3.6625 | 0.3766 |
| 3.6283 | 6.0 | 9768 | 3.6260 | 0.3791 |
| 3.5688 | 7.0 | 11396 | 3.6009 | 0.3825 |
| 3.5272 | 8.0 | 13024 | 3.5843 | 0.3835 |
| 3.499 | 9.0 | 14652 | 3.5737 | 0.3850 |
| 3.4752 | 10.0 | 16280 | 3.5684 | 0.3855 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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