GPT2-705M
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.6046
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: 300
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 8.0336 | 1.0 | 3 | 7.3770 |
| 6.2535 | 2.0 | 6 | 6.3128 |
| 5.6213 | 3.0 | 9 | 5.6716 |
| 4.8242 | 4.0 | 12 | 5.1521 |
| 4.6266 | 5.0 | 15 | 4.9789 |
| 4.4097 | 6.0 | 18 | 4.7306 |
| 4.0358 | 7.0 | 21 | 4.5332 |
| 4.0027 | 8.0 | 24 | 4.4014 |
| 3.8638 | 9.0 | 27 | 4.1175 |
| 3.5414 | 10.0 | 30 | 4.0355 |
| 3.4701 | 11.0 | 33 | 3.8834 |
| 3.4822 | 12.0 | 36 | 3.8336 |
| 3.0602 | 13.0 | 39 | 3.7213 |
| 3.1109 | 14.0 | 42 | 3.7379 |
| 2.9087 | 15.0 | 45 | 3.7389 |
| 2.7124 | 16.0 | 48 | 3.6220 |
| 2.5867 | 17.0 | 51 | 3.7192 |
| 2.4577 | 18.0 | 54 | 3.5953 |
| 2.279 | 19.0 | 57 | 3.7648 |
| 2.3218 | 20.0 | 60 | 3.6046 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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