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unlearn_nlvr2_vilt_random_label_4_87
jialicheng/unlearn_nlvr2_vilt_random_label_4_87
unlearn_nlvr2_vilt_random_label_4_87 is a machine learning model from jialicheng. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- vilt
- Access
- Public
- Created
- Oct 24, 2025
- Updated
- Oct 24, 2025
- SHA
- 67ac4b63
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
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: 1.1287
- Accuracy: 0.7323
- Dt Accuracy: 0.7323
- Df Accuracy: 0.4577
- Unlearn Overall Accuracy: 0.9191
- 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 |
|---|---|---|---|---|---|---|---|
| 0.2603 | 1.0 | 2700 | 0.6120 | 0.8155 | 0.6795 | 0.6795 | None |
| 0.196 | 2.0 | 5400 | 0.7421 | 0.6485 | 0.8067 | 0.8067 | None |
| 0.1365 | 3.0 | 8100 | 0.9205 | 0.5435 | 0.8720 | 0.8720 | None |
| 0.097 | 4.0 | 10800 | 1.0703 | 0.4840 | 0.9051 | 0.9051 | None |
| 0.0817 | 5.0 | 13500 | 1.1287 | 0.4577 | 0.9191 | 0.9191 | None |
Framework versions
- Transformers 4.48.0
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.21.0
- Library
- transformers
- Type
- vilt
- License
- apache-2.0
- Created
- Oct 24, 2025
- Updated
- Oct 24, 2025