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unlearn_cifar100_swin-base_bad_teaching_2_87
jialicheng/unlearn_cifar100_swin-base_bad_teaching_2_87
unlearn_cifar100_swin-base_bad_teaching_2_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: 13.0270
- Accuracy: 0.3061
- Dt Accuracy: 0.3061
- Df Accuracy: 0.194
- 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 | 16 | 1.5558 | 0.693 | 0 | 0 | None |
| No log | 2.0 | 32 | 1.5415 | 0.686 | 0 | 0 | None |
| No log | 3.0 | 48 | 1.8880 | 0.661 | 0 | 0 | None |
| No log | 4.0 | 64 | 2.3622 | 0.618 | 0 | 0 | None |
| No log | 5.0 | 80 | 3.2308 | 0.529 | 0 | 0 | None |
| No log | 6.0 | 96 | 3.3136 | 0.541 | 0 | 0 | None |
| No log | 7.0 | 112 | 3.8720 | 0.495 | 0 | 0 | None |
| No log | 8.0 | 128 | 3.7642 | 0.509 | 0 | 0 | None |
| No log | 9.0 | 144 | 4.3507 | 0.468 | 0 | 0 | None |
| No log | 10.0 | 160 | 5.2100 | 0.417 | 0 | 0 | None |
| No log | 11.0 | 176 | 5.5091 | 0.397 | 0 | 0 | None |
| No log | 12.0 | 192 | 6.1317 | 0.352 | 0 | 0 | None |
| No log | 13.0 | 208 | 6.8544 | 0.327 | 0 | 0 | None |
| No log | 14.0 | 224 | 8.7042 | 0.29 | 0 | 0 | None |
| No log | 15.0 | 240 | 8.6705 | 0.278 | 0 | 0 | None |
| No log | 16.0 | 256 | 8.6764 | 0.257 | 0 | 0 | None |
| No log | 17.0 | 272 | 9.9202 | 0.241 | 0 | 0 | None |
| No log | 18.0 | 288 | 11.7378 | 0.206 | 0 | 0 | None |
| No log | 19.0 | 304 | 11.2166 | 0.212 | 0 | 0 | None |
| No log | 20.0 | 320 | 13.0270 | 0.194 | 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