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recipe-distilbert-i
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0288
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: 2e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.3931 | 1.0 | 152 | 1.7738 |
| 1.7533 | 2.0 | 304 | 1.5109 |
| 1.5584 | 3.0 | 456 | 1.4003 |
| 1.443 | 4.0 | 608 | 1.3296 |
| 1.3551 | 5.0 | 760 | 1.2270 |
| 1.2981 | 6.0 | 912 | 1.1870 |
| 1.2577 | 7.0 | 1064 | 1.1511 |
| 1.2216 | 8.0 | 1216 | 1.1298 |
| 1.1958 | 9.0 | 1368 | 1.1087 |
| 1.1685 | 10.0 | 1520 | 1.0858 |
| 1.1533 | 11.0 | 1672 | 1.0820 |
| 1.1358 | 12.0 | 1824 | 1.0659 |
| 1.1286 | 13.0 | 1976 | 1.0382 |
| 1.1128 | 14.0 | 2128 | 1.0468 |
| 1.11 | 15.0 | 2280 | 1.0399 |
| 1.094 | 16.0 | 2432 | 1.0382 |
| 1.0969 | 17.0 | 2584 | 1.0096 |
| 1.0868 | 18.0 | 2736 | 1.0235 |
| 1.0845 | 19.0 | 2888 | 1.0227 |
| 1.0855 | 20.0 | 3040 | 1.0288 |
Framework versions
- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
