MNLI
This model is a fine-tuned version of google-t5/t5-base on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.4611
- Accuracy: 0.8686
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 | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.3694 | 1.0 | 12272 | 0.8565 | 0.3870 |
| 0.303 | 2.0 | 24544 | 0.8651 | 0.3789 |
| 0.2549 | 3.0 | 36816 | 0.8649 | 0.4213 |
| 0.2118 | 4.0 | 49088 | 0.8657 | 0.4461 |
| 0.1733 | 5.0 | 61360 | 0.8659 | 0.4700 |
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-MNLI
Base model
google-t5/t5-base