Downloads · 30 days
4
6% of all-time downloads
unlearn-so_cifar10_swin-base_random_label_6_87
jialicheng/unlearn-so_cifar10_swin-base_random_label_6_87
unlearn-so_cifar10_swin-base_random_label_6_87 is a image classification model from jialicheng. Use it when you need a label for an image. 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. --
All-time downloads
70
Public
Parameters
86.8M
350 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors348 MB · 99%
Parameter types
How the weights are stored.
F3286.8M · 100%
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 microsoft/swin-base-patch4-window7-224 on the cifar10 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1207
- Accuracy: 0.9769
- Dt Accuracy: 0.9769
- Df Accuracy: 0.7893
- Unlearn Overall Accuracy: 0.4725
- 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 256
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 391 | 0.1615 | 0.9623 | 0.2412 | 0.2412 | None |
| 0.6135 | 2.0 | 782 | 0.1615 | 0.9743 | 0.2227 | 0.2227 | None |
| 0.546 | 3.0 | 1173 | 0.1423 | 0.9773 | 0.2181 | 0.2181 | None |
| 0.4974 | 4.0 | 1564 | 0.1341 | 0.98 | 0.2140 | 0.2140 | None |
| 0.4974 | 5.0 | 1955 | 0.1264 | 0.978 | 0.2171 | 0.2171 | None |
| 0.4556 | 6.0 | 2346 | 0.1434 | 0.9633 | 0.2400 | 0.2400 | None |
| 0.4085 | 7.0 | 2737 | 0.1187 | 0.9597 | 0.2458 | 0.2458 | None |
| 0.3774 | 8.0 | 3128 | 0.1326 | 0.895 | 0.3396 | 0.3396 | None |
| 0.3322 | 9.0 | 3519 | 0.1177 | 0.8307 | 0.4233 | 0.4233 | None |
| 0.3322 | 10.0 | 3910 | 0.1207 | 0.7893 | 0.4725 | 0.4725 | None |
Framework versions
- Transformers 4.48.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.21.0
- Task
- Image Classification
- Library
- transformers
- Type
- swin
- License
- apache-2.0
- Created
- Oct 29, 2025
- Updated
- Oct 29, 2025