recipe-roberta-s
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8870
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 |
|---|---|---|---|
| 1.3387 | 1.0 | 820 | 1.1529 |
| 1.187 | 2.0 | 1640 | 1.0643 |
| 1.1213 | 3.0 | 2460 | 1.0371 |
| 1.0859 | 4.0 | 3280 | 1.0000 |
| 1.0566 | 5.0 | 4100 | 0.9798 |
| 1.0338 | 6.0 | 4920 | 0.9637 |
| 1.0162 | 7.0 | 5740 | 0.9538 |
| 1.0003 | 8.0 | 6560 | 0.9332 |
| 0.9878 | 9.0 | 7380 | 0.9252 |
| 0.9767 | 10.0 | 8200 | 0.9189 |
| 0.9664 | 11.0 | 9020 | 0.9145 |
| 0.9627 | 12.0 | 9840 | 0.9065 |
| 0.9539 | 13.0 | 10660 | 0.9027 |
| 0.9461 | 14.0 | 11480 | 0.9029 |
| 0.9435 | 15.0 | 12300 | 0.8949 |
| 0.9404 | 16.0 | 13120 | 0.8924 |
| 0.9359 | 17.0 | 13940 | 0.8874 |
| 0.9307 | 18.0 | 14760 | 0.8842 |
| 0.9295 | 19.0 | 15580 | 0.8853 |
| 0.9263 | 20.0 | 16400 | 0.8870 |
Framework versions
- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1