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unlearn_cifar100_swin-base_bad_teaching_6_87
jialicheng/unlearn_cifar100_swin-base_bad_teaching_6_87
unlearn_cifar100_swin-base_bad_teaching_6_87 is a image classification model from jialicheng. Use it when you need a label for an image. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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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 microsoft/swin-base-patch4-window7-224 on the cifar100 dataset. It achieves the following results on the evaluation set:
- Loss: 31.8912
- Accuracy: 0.1549
- Dt Accuracy: 0.1549
- Df Accuracy: 0.129
- Unlearn Overall Accuracy: 0
- 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: 0.0002
- train_batch_size: 128
- eval_batch_size: 256
- seed: 87
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 47 | 1.7923 | 0.6683 | 0 | 0 | None |
| No log | 2.0 | 94 | 2.9288 | 0.5933 | 0 | 0 | None |
| No log | 3.0 | 141 | 4.3632 | 0.501 | 0 | 0 | None |
| No log | 4.0 | 188 | 5.7233 | 0.4307 | 0 | 0 | None |
| No log | 5.0 | 235 | 8.0229 | 0.337 | 0 | 0 | None |
| No log | 6.0 | 282 | 9.1625 | 0.3093 | 0 | 0 | None |
| No log | 7.0 | 329 | 10.2969 | 0.29 | 0 | 0 | None |
| No log | 8.0 | 376 | 12.4993 | 0.2543 | 0 | 0 | None |
| No log | 9.0 | 423 | 12.8696 | 0.226 | 0 | 0 | None |
| No log | 10.0 | 470 | 16.9163 | 0.193 | 0 | 0 | None |
| 0.0 | 11.0 | 517 | 15.8142 | 0.2147 | 0 | 0 | None |
| 0.0 | 12.0 | 564 | 19.5163 | 0.1803 | 0 | 0 | None |
| 0.0 | 13.0 | 611 | 21.9126 | 0.166 | 0 | 0 | None |
| 0.0 | 14.0 | 658 | 21.9236 | 0.1757 | 0 | 0 | None |
| 0.0 | 15.0 | 705 | 21.8337 | 0.1727 | 0 | 0 | None |
| 0.0 | 16.0 | 752 | 25.1723 | 0.1467 | 0 | 0 | None |
| 0.0 | 17.0 | 799 | 27.3784 | 0.1337 | 0 | 0 | None |
| 0.0 | 18.0 | 846 | 28.0429 | 0.1367 | 0 | 0 | None |
| 0.0 | 19.0 | 893 | 30.5227 | 0.1303 | 0 | 0 | None |
| 0.0 | 20.0 | 940 | 31.8912 | 0.129 | 0 | 0 | None |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Image Classification
- Type
- swin
- License
- apache-2.0
- Created
- Oct 22, 2025
- Updated
- Oct 22, 2025