gpt2_small_AR_superbpe_32768_parallel3_42
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.8632
- Accuracy: 0.3286
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 |
|---|---|---|---|---|
| 4.4426 | 1.0 | 24819 | 4.3485 | 0.2788 |
| 4.2274 | 2.0 | 49638 | 4.1522 | 0.2973 |
| 4.1231 | 3.0 | 74457 | 4.0618 | 0.3064 |
| 4.0558 | 4.0 | 99276 | 4.0049 | 0.3121 |
| 4.0052 | 5.0 | 124095 | 3.9644 | 0.3165 |
| 3.9688 | 6.0 | 148914 | 3.9341 | 0.3200 |
| 3.9359 | 7.0 | 173733 | 3.9102 | 0.3227 |
| 3.9093 | 8.0 | 198552 | 3.8890 | 0.3253 |
| 3.88 | 9.0 | 223371 | 3.8723 | 0.3275 |
| 3.8603 | 10.0 | 248190 | 3.8632 | 0.3286 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.19.1
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