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jialicheng/
unlearn-so_cifar100_swin-base_salun_2_42

Name: unlearn-so_cifar100_swin-base_salun_2_42
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

endpoints_compatible

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42

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: 0.3086
Accuracy: 0.9236
Dt Accuracy: 0.9236
Df Accuracy: 0.609
Unlearn Overall Accuracy: 0.5714
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
0.8735	1.0	391	0.3352	0.82	0.3180	0.3180	None
0.7638	2.0	782	0.3412	0.792	0.3563	0.3563	None
0.6774	3.0	1173	0.3410	0.806	0.3376	0.3376	None
0.6276	4.0	1564	0.3224	0.765	0.3925	0.3925	None
0.571	5.0	1955	0.3295	0.746	0.4166	0.4166	None
0.5063	6.0	2346	0.3240	0.71	0.4603	0.4603	None
0.4828	7.0	2737	0.3151	0.679	0.4962	0.4962	None
0.4498	8.0	3128	0.3088	0.651	0.5272	0.5272	None
0.4142	9.0	3519	0.3107	0.628	0.5516	0.5516	None
0.3863	10.0	3910	0.3086	0.609	0.5714	0.5714	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_salun_2_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_salun_2_42