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gpt2-concat-guten-rarity-all-no-cut
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.3108
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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.6956 | 0.29 | 500 | 5.6386 |
| 5.345 | 0.58 | 1000 | 5.1997 |
| 4.9879 | 0.87 | 1500 | 4.9461 |
| 4.7107 | 1.16 | 2000 | 4.8083 |
| 4.5624 | 1.46 | 2500 | 4.6749 |
| 4.4461 | 1.75 | 3000 | 4.5687 |
| 4.3282 | 2.04 | 3500 | 4.4920 |
| 4.126 | 2.33 | 4000 | 4.4462 |
| 4.1006 | 2.62 | 4500 | 4.3882 |
| 4.0608 | 2.91 | 5000 | 4.3389 |
| 3.867 | 3.2 | 5500 | 4.3278 |
| 3.7992 | 3.49 | 6000 | 4.2984 |
| 3.7877 | 3.79 | 6500 | 4.2657 |
| 3.697 | 4.08 | 7000 | 4.2627 |
| 3.5135 | 4.37 | 7500 | 4.2592 |
| 3.5116 | 4.66 | 8000 | 4.2437 |
| 3.497 | 4.95 | 8500 | 4.2301 |
| 3.3453 | 5.24 | 9000 | 4.2423 |
| 3.3233 | 5.53 | 9500 | 4.2414 |
| 3.3142 | 5.82 | 10000 | 4.2405 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
