GPT2-705M
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.5063
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: 0.00025
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.8119 | 1.0 | 3 | 6.8091 |
| 6.6598 | 2.0 | 6 | 6.8246 |
| 6.0219 | 3.0 | 9 | 6.2434 |
| 5.1608 | 4.0 | 12 | 5.4866 |
| 4.6874 | 5.0 | 15 | 5.7119 |
| 4.7554 | 6.0 | 18 | 4.9916 |
| 4.3244 | 7.0 | 21 | 4.8076 |
| 4.3358 | 8.0 | 24 | 4.7170 |
| 4.3353 | 9.0 | 27 | 4.4035 |
| 4.0477 | 10.0 | 30 | 4.1959 |
| 3.7513 | 11.0 | 33 | 3.9729 |
| 3.7101 | 12.0 | 36 | 3.8325 |
| 3.333 | 13.0 | 39 | 3.7540 |
| 3.3225 | 14.0 | 42 | 3.6116 |
| 2.9902 | 15.0 | 45 | 3.5063 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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