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fine-tuned-DatasetQAS-TYDI-QA-ID-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: 0.9402
- Exact Match: 69.3662
- F1: 82.0036
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 |
|---|---|---|---|---|---|
| 6.2837 | 0.5 | 19 | 3.6986 | 8.4507 | 17.7536 |
| 6.2837 | 0.99 | 38 | 2.5899 | 18.4859 | 29.7766 |
| 3.6833 | 1.5 | 57 | 1.7044 | 42.6056 | 56.8157 |
| 3.6833 | 1.99 | 76 | 1.2711 | 53.3451 | 70.2979 |
| 3.6833 | 2.5 | 95 | 1.1063 | 62.3239 | 75.7765 |
| 1.5024 | 2.99 | 114 | 1.0275 | 64.2606 | 78.0460 |
| 1.5024 | 3.5 | 133 | 0.9941 | 65.8451 | 79.1313 |
| 1.0028 | 3.99 | 152 | 0.9642 | 67.4296 | 80.6196 |
| 1.0028 | 4.5 | 171 | 0.9682 | 69.0141 | 82.4975 |
| 1.0028 | 4.99 | 190 | 0.9455 | 67.9577 | 81.0386 |
| 0.7765 | 5.5 | 209 | 0.9802 | 67.7817 | 81.0844 |
| 0.7765 | 5.99 | 228 | 0.9402 | 69.3662 | 82.0036 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
