deberta-base-finetuned-squad-v2
This model is a fine-tuned version of microsoft/deberta-base on the squad_v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9221
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: 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 |
---|---|---|---|
0.753 | 1.0 | 8238 | 0.7286 |
0.5378 | 2.0 | 16476 | 0.7578 |
0.3881 | 3.0 | 24714 | 0.9221 |
Performance
- 'exact': 81.84115219405373
- 'f1': 85.19125695340612
- 'total': 11873
- 'HasAns_exact': 80.24628879892038
- 'HasAns_f1': 86.95610556811602
- 'HasAns_total': 5928
- 'NoAns_exact': 83.43145500420522
- 'NoAns_f1': 83.43145500420522
- 'NoAns_total': 5945
- 'best_exact': 81.84115219405373
- 'best_exact_thresh': 0.9994916319847107
- 'best_f1': 85.19125695340657
- 'best_f1_thresh': 0.9994916319847107
- 'total_time_in_seconds': 294.34524957099984
- 'samples_per_second': 40.33698528277447
- 'latency_in_seconds': 0.024791143735450168
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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