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fine-tuned-DatasetQAS-IDK-MRC-with-xlm-roberta-large-with-ITTL-without-freeze-LR-1e-05
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: 0.8090
- Exact Match: 74.0838
- F1: 80.8517
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 | Exact Match | F1 |
|---|---|---|---|---|---|
| 6.1945 | 0.49 | 36 | 2.3430 | 50.0 | 50.0 |
| 3.5404 | 0.98 | 72 | 1.8265 | 48.5602 | 52.5772 |
| 1.9365 | 1.48 | 108 | 1.2750 | 59.4241 | 67.2505 |
| 1.9365 | 1.97 | 144 | 1.0492 | 66.0995 | 73.9501 |
| 1.2265 | 2.46 | 180 | 0.9042 | 69.7644 | 77.5779 |
| 0.9482 | 2.95 | 216 | 0.8393 | 71.2042 | 78.9342 |
| 0.7866 | 3.45 | 252 | 0.8805 | 70.8115 | 78.2310 |
| 0.7866 | 3.94 | 288 | 0.9333 | 69.5026 | 76.5121 |
| 0.6871 | 4.44 | 324 | 0.8045 | 75.3927 | 82.4815 |
| 0.6086 | 4.92 | 360 | 0.7908 | 75.5236 | 81.8859 |
| 0.6086 | 5.42 | 396 | 0.8351 | 73.0366 | 80.3624 |
| 0.5449 | 5.91 | 432 | 0.8090 | 74.0838 | 80.8517 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
