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cbt-mod-formatting-rarity-all-end-p5k
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.3141
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 |
|---|---|---|---|
| 6.6904 | 0.29 | 500 | 5.6437 |
| 5.3322 | 0.58 | 1000 | 5.2055 |
| 4.99 | 0.88 | 1500 | 4.9612 |
| 4.7191 | 1.17 | 2000 | 4.8075 |
| 4.5537 | 1.46 | 2500 | 4.6852 |
| 4.4476 | 1.75 | 3000 | 4.5760 |
| 4.3289 | 2.04 | 3500 | 4.4999 |
| 4.1221 | 2.33 | 4000 | 4.4489 |
| 4.1042 | 2.63 | 4500 | 4.3930 |
| 4.0527 | 2.92 | 5000 | 4.3419 |
| 3.8583 | 3.21 | 5500 | 4.3364 |
| 3.7948 | 3.5 | 6000 | 4.3044 |
| 3.783 | 3.79 | 6500 | 4.2724 |
| 3.6942 | 4.08 | 7000 | 4.2664 |
| 3.5141 | 4.38 | 7500 | 4.2599 |
| 3.5062 | 4.67 | 8000 | 4.2461 |
| 3.4973 | 4.96 | 8500 | 4.2347 |
| 3.3442 | 5.25 | 9000 | 4.2477 |
| 3.3187 | 5.54 | 9500 | 4.2463 |
| 3.3148 | 5.83 | 10000 | 4.2447 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
