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jialicheng/
unlearn_cifar100_swin-base_salun_10_87

Name: unlearn_cifar100_swin-base_salun_10_87
Availability: InStock

generated_from_trainer

microsoft/swin-base-patch4-window7-224

finetune

apache-2.0

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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: 0.4739
Accuracy: 0.8801
Dt Accuracy: 0.8801
Df Accuracy: 0.184
Unlearn Overall Accuracy: 0.8837
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	391	0.5238	0.7584	0.3971	0.3971	None
1.3495	2.0	782	0.4766	0.775	0.3771	0.3771	None
1.1537	3.0	1173	0.4893	0.7512	0.4064	0.4064	None
1.0428	4.0	1564	0.4963	0.7404	0.4197	0.4197	None
1.0428	5.0	1955	0.4708	0.745	0.4148	0.4148	None
0.9603	6.0	2346	0.4898	0.7022	0.4653	0.4653	None
0.8735	7.0	2737	0.5133	0.6524	0.5184	0.5184	None
0.816	8.0	3128	0.5102	0.5736	0.5954	0.5954	None
0.7412	9.0	3519	0.5291	0.5488	0.6180	0.6180	None
0.7412	10.0	3910	0.5438	0.4676	0.6841	0.6841	None
0.6762	11.0	4301	0.5077	0.438	0.7110	0.7110	None
0.6223	12.0	4692	0.4952	0.379	0.7549	0.7549	None
0.5729	13.0	5083	0.5299	0.3384	0.7794	0.7794	None
0.5729	14.0	5474	0.5143	0.2962	0.8110	0.8110	None
0.5351	15.0	5865	0.5089	0.2476	0.8414	0.8414	None
0.4842	16.0	6256	0.4973	0.2372	0.8496	0.8496	None
0.4559	17.0	6647	0.4807	0.217	0.8631	0.8631	None
0.4231	18.0	7038	0.4787	0.1966	0.8747	0.8747	None
0.4231	19.0	7429	0.4786	0.1806	0.8846	0.8846	None
0.3947	20.0	7820	0.4739	0.184	0.8837	0.8837	None

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu118
Datasets 2.18.0
Tokenizers 0.15.2

jialicheng/unlearn_cifar100_swin-base_salun_10_87

87

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jialicheng/
unlearn_cifar100_swin-base_salun_10_87