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all-base-rarity-all-iorder-5p5k-rerun
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.1275
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 |
---|---|---|---|
6.4732 | 0.31 | 500 | 5.3516 |
5.1494 | 0.63 | 1000 | 4.9437 |
4.8252 | 0.94 | 1500 | 4.7060 |
4.5437 | 1.25 | 2000 | 4.5574 |
4.4086 | 1.56 | 2500 | 4.4339 |
4.2985 | 1.88 | 3000 | 4.3371 |
4.0975 | 2.19 | 3500 | 4.2737 |
4.0101 | 2.5 | 4000 | 4.2143 |
3.9741 | 2.82 | 4500 | 4.1609 |
3.8328 | 3.13 | 5000 | 4.1351 |
3.7097 | 3.44 | 5500 | 4.1108 |
3.6861 | 3.75 | 6000 | 4.0766 |
3.6091 | 4.07 | 6500 | 4.0649 |
3.4234 | 4.38 | 7000 | 4.0613 |
3.4183 | 4.69 | 7500 | 4.0456 |
3.4039 | 5.01 | 8000 | 4.0343 |
3.2378 | 5.32 | 8500 | 4.0448 |
3.234 | 5.63 | 9000 | 4.0441 |
3.2304 | 5.94 | 9500 | 4.0428 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3