bart-large-bn-adapter-3.17M-snli-model3
This model is a fine-tuned version of facebook/bart-large on the snli dataset. It achieves the following results on the evaluation set:
- Loss: 0.2384
- Accuracy: 0.9171
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: 5
- 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 |
|---|---|---|---|---|
| 0.3391 | 1.0 | 17168 | 0.2519 | 0.9111 |
| 0.3134 | 2.0 | 34336 | 0.2398 | 0.9162 |
| 0.3057 | 3.0 | 51504 | 0.2384 | 0.9171 |
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/bart-large-bn-adapter-3.17M-snli-model3
Base model
facebook/bart-large