42
This model is a fine-tuned version of dandelin/vilt-b32-finetuned-nlvr2 on the nlvr2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5265
- Accuracy: 0.7343
- Dt Accuracy: 0.7343
- Df Accuracy: 0.8677
- Unlearn Overall Accuracy: 0.6290
- Unlearn Time: None
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 216 | 0.5532 | 0.8941 | 0.6044 | 0.6044 | None |
| No log | 2.0 | 432 | 0.5348 | 0.8991 | 0.6012 | 0.6012 | None |
| 0.4692 | 3.0 | 648 | 0.5280 | 0.8872 | 0.6121 | 0.6121 | None |
| 0.4692 | 4.0 | 864 | 0.5273 | 0.8677 | 0.6289 | 0.6289 | None |
| 0.2457 | 5.0 | 1080 | 0.5265 | 0.8677 | 0.6290 | 0.6290 | None |
Framework versions
- Transformers 4.48.0
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.21.0
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Base model
dandelin/vilt-b32-finetuned-nlvr2