87
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: 0.9531
- Accuracy: 0.7340
- Dt Accuracy: 0.7340
- Df Accuracy: 0.4942
- Unlearn Overall Accuracy: 0.8993
- 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: 87
- 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 |
|---|---|---|---|---|---|---|---|
| 0.3083 | 1.0 | 2700 | 0.5634 | 0.8494 | 0.6491 | 0.6491 | None |
| 0.2489 | 2.0 | 5400 | 0.6488 | 0.7106 | 0.7621 | 0.7621 | None |
| 0.1875 | 3.0 | 8100 | 0.7737 | 0.5891 | 0.8444 | 0.8444 | None |
| 0.1474 | 4.0 | 10800 | 0.9183 | 0.5195 | 0.8851 | 0.8851 | None |
| 0.1233 | 5.0 | 13500 | 0.9531 | 0.4942 | 0.8993 | 0.8993 | 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