roberta-base-finetuned-squad-v2
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8475
{"exact": 78.50585361745136, "f1": 81.58359022842608, "total": 11873, "HasAns_exact": 77.71592442645074, "HasAns_f1": 83.8802238161443, "HasAns_total": 5928, "NoAns_exact": 79.29352396972246, "NoAns_f1": 79.29352396972246, "NoAns_total": 5945, "best_exact": 79.41548050197927, "best_exact_thresh": 0.17161580696895154, "best_f1": 82.14757970157191, "best_f1_thresh": 0.17426970650172677, "pr_exact_ap": 65.90521604124024, "pr_f1_ap": 75.35707443729065, "pr_oracle_ap": 91.89035655865922}
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9481 | 0.9996 | 2059 | 0.8358 |
| 0.7421 | 1.9998 | 4119 | 0.8362 |
| 0.6294 | 2.9989 | 6177 | 0.8475 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1