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gpt2-concat-guten-rarity-no-cut-corrected
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.3120
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 |
|---|---|---|---|
| 6.7039 | 0.29 | 500 | 5.6444 |
| 5.3477 | 0.58 | 1000 | 5.1977 |
| 4.9877 | 0.87 | 1500 | 4.9542 |
| 4.7147 | 1.16 | 2000 | 4.8034 |
| 4.5565 | 1.46 | 2500 | 4.6723 |
| 4.4503 | 1.75 | 3000 | 4.5667 |
| 4.3289 | 2.04 | 3500 | 4.4930 |
| 4.1305 | 2.33 | 4000 | 4.4433 |
| 4.0991 | 2.62 | 4500 | 4.3879 |
| 4.0629 | 2.91 | 5000 | 4.3392 |
| 3.8648 | 3.2 | 5500 | 4.3323 |
| 3.8005 | 3.49 | 6000 | 4.2991 |
| 3.7818 | 3.79 | 6500 | 4.2701 |
| 3.6998 | 4.08 | 7000 | 4.2639 |
| 3.5113 | 4.37 | 7500 | 4.2592 |
| 3.5113 | 4.66 | 8000 | 4.2454 |
| 3.5008 | 4.95 | 8500 | 4.2317 |
| 3.3469 | 5.24 | 9000 | 4.2439 |
| 3.3188 | 5.53 | 9500 | 4.2429 |
| 3.3168 | 5.82 | 10000 | 4.2418 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
