t5-base-bn-adapter-1.79M-snli-model1
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7158
- Accuracy: 0.748
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: 6
- 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 |
---|---|---|---|---|
0.4121 | 1.0 | 8584 | 0.3389 | 0.8761 |
0.3881 | 2.0 | 17168 | 0.3116 | 0.8853 |
0.3692 | 3.0 | 25752 | 0.3075 | 0.8871 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
Model tree for varun-v-rao/t5-base-bn-adapter-1.79M-snli-model1
Base model
google-t5/t5-base