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fine-tuned-DatasetQAS-Squad-ID-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: 1.3876
- Exact Match: 53.6102
- F1: 69.6077
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 64
- 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 |
---|---|---|---|---|---|
1.5313 | 0.5 | 463 | 1.4235 | 48.7014 | 66.1658 |
1.3868 | 1.0 | 926 | 1.3193 | 51.7189 | 68.5896 |
1.2618 | 1.5 | 1389 | 1.2877 | 52.8032 | 69.3561 |
1.1847 | 2.0 | 1852 | 1.2893 | 53.0218 | 69.7724 |
1.0884 | 2.5 | 2315 | 1.2777 | 53.3328 | 69.8210 |
1.0927 | 3.0 | 2778 | 1.2596 | 53.4000 | 69.9664 |
0.9519 | 3.5 | 3241 | 1.3342 | 53.6102 | 69.6168 |
0.9591 | 4.0 | 3704 | 1.3078 | 54.0640 | 69.9492 |
0.8586 | 4.49 | 4167 | 1.3876 | 53.6102 | 69.6077 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2