QNLI
This model is a fine-tuned version of google-t5/t5-base on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.2215
- Accuracy: 0.9282
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-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2856 | 1.0 | 1637 | 0.2216 | 0.9149 |
| 0.2258 | 2.0 | 3274 | 0.2060 | 0.9220 |
| 0.1791 | 3.0 | 4911 | 0.2038 | 0.9277 |
| 0.1476 | 4.0 | 6548 | 0.2215 | 0.9282 |
| 0.1263 | 5.0 | 8185 | 0.2301 | 0.9279 |
Framework versions
- Transformers 4.43.3
- Pytorch 1.11.0+cu113
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for du33169/t5-base-finetuned-GLUE-QNLI
Base model
google-t5/t5-base