<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
MTL-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: 1.4859
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 |
---|---|---|---|
1.8338 | 1.0 | 98 | 1.6750 |
1.7732 | 2.0 | 196 | 1.6229 |
1.7208 | 3.0 | 294 | 1.6131 |
1.6917 | 4.0 | 392 | 1.5936 |
1.6579 | 5.0 | 490 | 1.6183 |
1.6246 | 6.0 | 588 | 1.6015 |
1.6215 | 7.0 | 686 | 1.5248 |
1.5743 | 8.0 | 784 | 1.5454 |
1.5621 | 9.0 | 882 | 1.5925 |
1.5652 | 10.0 | 980 | 1.5213 |
1.5615 | 11.0 | 1078 | 1.4845 |
1.5349 | 12.0 | 1176 | 1.5443 |
1.5165 | 13.0 | 1274 | 1.5304 |
1.5164 | 14.0 | 1372 | 1.4773 |
1.5293 | 15.0 | 1470 | 1.5537 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0