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recipe-roberta-upper-tIs
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7904
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 |
|---|---|---|---|
| 1.2671 | 1.0 | 1281 | 1.0554 |
| 1.0995 | 2.0 | 2562 | 0.9832 |
| 1.0339 | 3.0 | 3843 | 0.9389 |
| 0.9925 | 4.0 | 5124 | 0.9095 |
| 0.964 | 5.0 | 6405 | 0.8914 |
| 0.9426 | 6.0 | 7686 | 0.8708 |
| 0.9227 | 7.0 | 8967 | 0.8590 |
| 0.9082 | 8.0 | 10248 | 0.8448 |
| 0.8963 | 9.0 | 11529 | 0.8361 |
| 0.8847 | 10.0 | 12810 | 0.8249 |
| 0.8756 | 11.0 | 14091 | 0.8204 |
| 0.8672 | 12.0 | 15372 | 0.8105 |
| 0.8612 | 13.0 | 16653 | 0.8106 |
| 0.8561 | 14.0 | 17934 | 0.8041 |
| 0.8485 | 15.0 | 19215 | 0.7979 |
| 0.8452 | 16.0 | 20496 | 0.7910 |
| 0.8403 | 17.0 | 21777 | 0.7991 |
| 0.8389 | 18.0 | 23058 | 0.7928 |
| 0.8371 | 19.0 | 24339 | 0.7926 |
| 0.8341 | 20.0 | 25620 | 0.7904 |
Framework versions
- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
