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recipe-roberta-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: 0.8491
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 |
|---|---|---|---|
| 1.3552 | 1.0 | 1012 | 1.1292 |
| 1.1811 | 2.0 | 2024 | 1.0543 |
| 1.1095 | 3.0 | 3036 | 1.0122 |
| 1.0667 | 4.0 | 4048 | 0.9756 |
| 1.0345 | 5.0 | 5060 | 0.9478 |
| 1.0112 | 6.0 | 6072 | 0.9292 |
| 0.9922 | 7.0 | 7084 | 0.9137 |
| 0.9762 | 8.0 | 8096 | 0.9056 |
| 0.9627 | 9.0 | 9108 | 0.8977 |
| 0.9507 | 10.0 | 10120 | 0.8868 |
| 0.9411 | 11.0 | 11132 | 0.8823 |
| 0.9344 | 12.0 | 12144 | 0.8745 |
| 0.9261 | 13.0 | 13156 | 0.8688 |
| 0.9189 | 14.0 | 14168 | 0.8614 |
| 0.9133 | 15.0 | 15180 | 0.8609 |
| 0.9078 | 16.0 | 16192 | 0.8581 |
| 0.906 | 17.0 | 17204 | 0.8544 |
| 0.9015 | 18.0 | 18216 | 0.8537 |
| 0.8988 | 19.0 | 19228 | 0.8494 |
| 0.8975 | 20.0 | 20240 | 0.8491 |
Framework versions
- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
