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: 2.3233
Accuracy: 0.713
Dt Accuracy: 0.713
Df Accuracy: 0.6908
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: 5e-05
train_batch_size: 128
eval_batch_size: 256
seed: 42
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	79	0.7439	0.8744	0.2360	0.2360	None
0.0	2.0	158	0.9403	0.8504	0.2708	0.2708	None
0.0	3.0	237	1.0198	0.8372	0.2889	0.2889	None
0.0	4.0	316	1.1363	0.835	0.2918	0.2918	None
0.0	5.0	395	1.2559	0.8064	0.3296	0.3296	None
0.0	6.0	474	1.4729	0.781	0.3600	0.3600	None
0.0	7.0	553	1.9812	0.7262	0	0	None
0.0	8.0	632	2.0826	0.709	0	0	None
0.0	9.0	711	2.2011	0.7028	0	0	None
0.0	10.0	790	2.3233	0.6908	0	0	None

Framework versions

Transformers 4.48.0
Pytorch 2.2.2+cu118
Datasets 3.2.0
Tokenizers 0.21.0

jialicheng/unlearn-so_cifar100_swin-base_bad_teaching_10_42

42

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn-so_cifar100_swin-base_bad_teaching_10_42