unlearn_cifar100_resnet-50_random_label_2_42 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar100_resnet-50_random_label_2_42

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image-classification

generated_from_trainer

microsoft/resnet-50

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This model is a fine-tuned version of microsoft/resnet-50 on the cifar100 dataset. It achieves the following results on the evaluation set:

Loss: 0.5456
Accuracy: 0.8396
Dt Accuracy: 0.8396
Df Accuracy: 0.907
Unlearn Overall Accuracy: 0.1616
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: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
1.146	1.0	391	0.5865	0.898	0.1678	0.1678	None
1.1193	2.0	782	0.5712	0.9	0.1666	0.1666	None
1.1058	3.0	1173	0.5706	0.896	0.1694	0.1694	None
1.0641	4.0	1564	0.5514	0.905	0.1631	0.1631	None
1.0401	5.0	1955	0.5528	0.9	0.1665	0.1665	None
1.0003	6.0	2346	0.5608	0.893	0.1714	0.1714	None
1.0065	7.0	2737	0.5465	0.905	0.1630	0.1630	None
0.9978	8.0	3128	0.5472	0.902	0.1651	0.1651	None
0.975	9.0	3519	0.5446	0.905	0.1630	0.1630	None
0.9475	10.0	3910	0.5456	0.907	0.1616	0.1616	None

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu118
Datasets 2.18.0
Tokenizers 0.15.2