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Model description
Finetuned on SQUAD2.0 Dataset
F1: 83.738696142672
Trained on single V100 GPU
Everyone is welcome to use~
Hope you have a nice day
Performance
HasAns_exact': 77.1255060728745, 'HasAns_f1': 83.87812741260885, 'HasAns_total': 5928,
'NoAns_exact': 83.59966358284272, 'NoAns_f1': 83.59966358284272, 'NoAns_total': 5945,
'best_exact': 80.36721974227238, 'best_exact_thresh': 0.0,
'best_f1': 83.7386961426719, 'best_f1_thresh': 0.0,
'exact': 80.36721974227238,
'f1': 83.738696142672,
'total': 11873
roberta-base-finetuned-squad2-lwt
This model is a fine-tuned version of roberta-base on the squad_v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9441
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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 |
|---|---|---|---|
| 0.871 | 1.0 | 8239 | 0.8156 |
| 0.6787 | 2.0 | 16478 | 0.8494 |
| 0.4867 | 3.0 | 24717 | 0.9441 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
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