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: 1.1383
- Accuracy: 0.7339
- Dt Accuracy: 0.7339
- Df Accuracy: 0.4571
- Unlearn Overall Accuracy: 0.9202
- 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 |
|---|---|---|---|---|---|---|---|
| 0.2576 | 1.0 | 2700 | 0.6234 | 0.8132 | 0.6807 | 0.6807 | None |
| 0.1895 | 2.0 | 5400 | 0.7204 | 0.6662 | 0.7941 | 0.7941 | None |
| 0.1368 | 3.0 | 8100 | 0.9241 | 0.5450 | 0.8711 | 0.8711 | None |
| 0.1023 | 4.0 | 10800 | 1.0661 | 0.4840 | 0.9061 | 0.9061 | None |
| 0.0821 | 5.0 | 13500 | 1.1383 | 0.4571 | 0.9202 | 0.9202 | None |
Framework versions
- Transformers 4.48.0
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.21.0
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dandelin/vilt-b32-finetuned-nlvr2