TExAS-SQuAD-is
This model is a fine-tuned version of IceBERT on the TExAS-SQuAD-is dataset. It achieves the following results on the evaluation set:
- Exact match: xx.xx%
- F1-score: xx.xx%
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.5353 | 0.12 | 500 | 2.2356 |
2.364 | 0.24 | 1000 | 2.0607 |
2.2243 | 0.36 | 1500 | 2.0617 |
2.1403 | 0.49 | 2000 | 1.9934 |
2.1491 | 0.61 | 2500 | 2.0515 |
2.0604 | 0.73 | 3000 | 1.9602 |
2.0232 | 0.85 | 3500 | 1.8954 |
2.0905 | 0.97 | 4000 | 1.9474 |
1.9229 | 1.09 | 4500 | 1.9814 |
1.9162 | 1.22 | 5000 | 1.9053 |
1.8937 | 1.34 | 5500 | 1.9501 |
1.9085 | 1.46 | 6000 | 1.8882 |
1.8671 | 1.58 | 6500 | 1.8996 |
1.8997 | 1.7 | 7000 | 1.8340 |
1.8546 | 1.82 | 7500 | 1.8883 |
1.8935 | 1.95 | 8000 | 1.8567 |
1.7031 | 2.07 | 8500 | 1.9206 |
1.7699 | 2.19 | 9000 | 1.8790 |
1.7016 | 2.31 | 9500 | 1.8670 |
1.7744 | 2.43 | 10000 | 1.8951 |
1.7518 | 2.55 | 10500 | 1.9550 |
1.7503 | 2.68 | 11000 | 1.9120 |
1.7818 | 2.8 | 11500 | 1.8820 |
1.6955 | 2.92 | 12000 | 1.8908 |
Framework versions
- Transformers 4.12.2
- Pytorch 1.8.1+cu101
- Datasets 1.12.1
- Tokenizers 0.10.3
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