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fine-tuned-NLI-idk-mrc-nli-keep-with-xlm-roberta-large
This model is a fine-tuned version of xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1224
- Accuracy: 0.9751
- F1: 0.9751
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.3634 | 0.49 | 39 | 0.6900 | 0.5052 | 0.3515 |
| 0.7309 | 0.99 | 78 | 0.2791 | 0.9202 | 0.9202 |
| 0.4815 | 1.49 | 117 | 0.0854 | 0.9738 | 0.9738 |
| 0.145 | 1.99 | 156 | 0.0903 | 0.9699 | 0.9699 |
| 0.145 | 2.49 | 195 | 0.0931 | 0.9738 | 0.9738 |
| 0.0937 | 2.99 | 234 | 0.0875 | 0.9751 | 0.9751 |
| 0.0752 | 3.49 | 273 | 0.1164 | 0.9738 | 0.9738 |
| 0.0538 | 3.99 | 312 | 0.1386 | 0.9673 | 0.9673 |
| 0.0379 | 4.49 | 351 | 0.0893 | 0.9791 | 0.9791 |
| 0.0379 | 4.99 | 390 | 0.1002 | 0.9777 | 0.9777 |
| 0.0397 | 5.49 | 429 | 0.1214 | 0.9764 | 0.9764 |
| 0.031 | 5.99 | 468 | 0.1224 | 0.9751 | 0.9751 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
