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fine-tuned-DatasetQAS-IDK-MRC-with-xlm-roberta-large-without-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: 0.8673
- Exact Match: 74.0838
- F1: 81.0390
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 32
- 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 |
---|---|---|---|---|---|
6.2177 | 0.49 | 36 | 2.3043 | 45.2880 | 46.1924 |
3.4831 | 0.98 | 72 | 1.5333 | 51.3089 | 56.5227 |
1.6897 | 1.48 | 108 | 1.1604 | 60.2094 | 68.3733 |
1.6897 | 1.97 | 144 | 0.9852 | 65.3141 | 72.9935 |
1.1108 | 2.46 | 180 | 0.9487 | 65.4450 | 72.8064 |
0.8854 | 2.95 | 216 | 0.8634 | 68.0628 | 75.1967 |
0.7269 | 3.45 | 252 | 0.9271 | 69.7644 | 76.9429 |
0.7269 | 3.94 | 288 | 0.9044 | 69.3717 | 76.4864 |
0.648 | 4.44 | 324 | 0.8352 | 73.1675 | 79.8410 |
0.5446 | 4.92 | 360 | 0.8074 | 74.7382 | 81.2181 |
0.5446 | 5.42 | 396 | 0.8726 | 73.4293 | 80.5400 |
0.497 | 5.91 | 432 | 0.8598 | 73.6911 | 80.8239 |
0.4647 | 6.41 | 468 | 0.8673 | 74.0838 | 81.0390 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2