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: 0.5263
- Accuracy: 0.7355
- Dt Accuracy: 0.7355
- Df Accuracy: 0.8759
- Unlearn Overall Accuracy: 0.6218
- 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 | 324 | 0.5474 | 0.9126 | 0.5881 | 0.5881 | None |
| 0.4885 | 2.0 | 648 | 0.5345 | 0.9118 | 0.5892 | 0.5892 | None |
| 0.4885 | 3.0 | 972 | 0.5297 | 0.8911 | 0.6089 | 0.6089 | None |
| 0.3043 | 4.0 | 1296 | 0.5268 | 0.8842 | 0.6147 | 0.6147 | None |
| 0.2354 | 5.0 | 1620 | 0.5263 | 0.8759 | 0.6218 | 0.6218 | 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