t5-base-mnli-model2
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9394
- Accuracy: 0.7175
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: 64
- eval_batch_size: 64
- seed: 74
- 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 | Accuracy |
|---|---|---|---|---|
| 0.3343 | 1.0 | 6136 | 0.3841 | 0.8606 |
| 0.2948 | 2.0 | 12272 | 0.3960 | 0.8640 |
| 0.2883 | 3.0 | 18408 | 0.3968 | 0.8659 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for varun-v-rao/t5-base-mnli-model2
Base model
google-t5/t5-base