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gpt2-concat-cbt-rarity-all-5p75k-p55k
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 3.1884
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 |
|---|---|---|---|
| 6.7274 | 0.29 | 500 | 5.6366 |
| 5.3729 | 0.59 | 1000 | 5.2059 |
| 5.0241 | 0.88 | 1500 | 4.9462 |
| 4.7442 | 1.17 | 2000 | 4.7999 |
| 4.5874 | 1.46 | 2500 | 4.6725 |
| 4.4736 | 1.76 | 3000 | 4.5694 |
| 4.3472 | 2.05 | 3500 | 4.4901 |
| 4.1581 | 2.34 | 4000 | 4.4410 |
| 4.1297 | 2.63 | 4500 | 4.3834 |
| 4.0798 | 2.93 | 5000 | 4.3289 |
| 3.883 | 3.22 | 5500 | 4.3259 |
| 3.8233 | 3.51 | 6000 | 4.2937 |
| 3.8044 | 3.8 | 6500 | 4.2585 |
| 3.7076 | 4.1 | 7000 | 4.2566 |
| 3.5409 | 4.39 | 7500 | 4.2515 |
| 3.5309 | 4.68 | 8000 | 4.2363 |
| 3.5148 | 4.97 | 8500 | 4.2237 |
| 3.3604 | 5.27 | 9000 | 4.2357 |
| 3.3405 | 5.56 | 9500 | 4.2344 |
| 3.3393 | 5.85 | 10000 | 4.2330 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
