FYP_sq2_mrqa
This model is a fine-tuned version of deepset/deberta-v3-base-squad2 on MRQA dataset. It achieves the following results on the evaluation set:
- Loss: 2.0805
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: 5e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.2667 | 0.14 | 4000 | 2.6882 |
| 2.4457 | 0.27 | 8000 | 2.3556 |
| 2.2012 | 0.41 | 12000 | 2.1995 |
| 2.0871 | 0.55 | 16000 | 2.1129 |
| 2.0249 | 0.68 | 20000 | 2.1128 |
| 1.9939 | 0.82 | 24000 | 2.0941 |
| 1.9658 | 0.95 | 28000 | 2.0805 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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