t5-large-bn-adapter-6.34M-snli-model1
This model is a fine-tuned version of t5-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6034
- Accuracy: 0.8005
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: 32
- eval_batch_size: 32
- seed: 40
- 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 |
---|---|---|---|---|
0.3118 | 1.0 | 17168 | 0.2381 | 0.9150 |
0.2742 | 2.0 | 34336 | 0.2299 | 0.9171 |
0.2725 | 3.0 | 51504 | 0.2277 | 0.9197 |
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-large-bn-adapter-6.34M-snli-model1
Base model
google-t5/t5-large