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gpt2-concat-mod-datasets1-iorder-rarity-all-5p5k
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.3832
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 |
|---|---|---|---|
| 6.7791 | 0.32 | 500 | 5.6460 |
| 5.4436 | 0.63 | 1000 | 5.2273 |
| 5.0944 | 0.95 | 1500 | 4.9700 |
| 4.809 | 1.26 | 2000 | 4.8294 |
| 4.6757 | 1.58 | 2500 | 4.7121 |
| 4.5526 | 1.9 | 3000 | 4.6044 |
| 4.3523 | 2.21 | 3500 | 4.5477 |
| 4.2579 | 2.53 | 4000 | 4.4848 |
| 4.2187 | 2.84 | 4500 | 4.4262 |
| 4.0519 | 3.16 | 5000 | 4.4090 |
| 3.9359 | 3.47 | 5500 | 4.3808 |
| 3.9128 | 3.79 | 6000 | 4.3460 |
| 3.8052 | 4.11 | 6500 | 4.3424 |
| 3.6404 | 4.42 | 7000 | 4.3367 |
| 3.6307 | 4.74 | 7500 | 4.3246 |
| 3.5885 | 5.05 | 8000 | 4.3236 |
| 3.4332 | 5.37 | 8500 | 4.3296 |
| 3.4351 | 5.69 | 9000 | 4.3281 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
