SAE-roberta-base
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6959
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: 7
- eval_batch_size: 7
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9847 | 1.0 | 79 | 1.8238 |
| 1.9142 | 2.0 | 158 | 1.8299 |
| 1.8613 | 3.0 | 237 | 1.7636 |
| 1.8384 | 4.0 | 316 | 1.8048 |
| 1.8193 | 5.0 | 395 | 1.7734 |
| 1.7985 | 6.0 | 474 | 1.7271 |
| 1.7758 | 7.0 | 553 | 1.8525 |
| 1.7611 | 8.0 | 632 | 1.7716 |
| 1.7599 | 9.0 | 711 | 1.7913 |
| 1.7118 | 10.0 | 790 | 1.7578 |
| 1.7003 | 11.0 | 869 | 1.7598 |
| 1.7072 | 12.0 | 948 | 1.6942 |
| 1.6511 | 13.0 | 1027 | 1.6955 |
| 1.6802 | 14.0 | 1106 | 1.7837 |
| 1.7048 | 15.0 | 1185 | 1.7377 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
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