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fine-tuned-DatasetQAS-TYDI-QA-ID-with-xlm-roberta-large-with-ITTL-with-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: 0.9154
- Exact Match: 67.4296
- F1: 80.7483
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 |
---|---|---|---|---|---|
6.331 | 0.5 | 19 | 3.7275 | 5.2817 | 16.4975 |
6.331 | 0.99 | 38 | 2.5293 | 22.3592 | 33.2570 |
3.6805 | 1.5 | 57 | 1.5504 | 45.4225 | 61.5302 |
3.6805 | 1.99 | 76 | 1.2025 | 57.2183 | 72.1651 |
3.6805 | 2.5 | 95 | 1.0664 | 61.0915 | 75.6496 |
1.3982 | 2.99 | 114 | 0.9926 | 63.2042 | 77.6464 |
1.3982 | 3.5 | 133 | 0.9823 | 64.6127 | 78.3848 |
0.9533 | 3.99 | 152 | 0.9596 | 66.1972 | 79.5651 |
0.9533 | 4.5 | 171 | 0.9578 | 67.4296 | 80.6710 |
0.9533 | 4.99 | 190 | 0.9376 | 68.3099 | 80.8025 |
0.7418 | 5.5 | 209 | 0.9393 | 67.4296 | 79.8821 |
0.7418 | 5.99 | 228 | 0.9242 | 67.4296 | 79.9318 |
0.7418 | 6.5 | 247 | 0.9154 | 67.4296 | 80.7483 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2