unlearn_cifar100_resnet-50_random_label_2_87 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar100_resnet-50_random_label_2_87

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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: 0.5404
Accuracy: 0.8408
Dt Accuracy: 0.8408
Df Accuracy: 0.895
Unlearn Overall Accuracy: 0.1699
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: 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
1.1594	1.0	391	0.5830	0.898	0.1679	0.1679	None
1.1158	2.0	782	0.5704	0.899	0.1673	0.1673	None
1.0827	3.0	1173	0.5639	0.899	0.1673	0.1673	None
1.05	4.0	1564	0.5543	0.888	0.1748	0.1748	None
1.0484	5.0	1955	0.5518	0.901	0.1658	0.1658	None
1.031	6.0	2346	0.5491	0.886	0.1761	0.1761	None
1.001	7.0	2737	0.5433	0.894	0.1706	0.1706	None
0.9714	8.0	3128	0.5412	0.893	0.1712	0.1712	None
0.9789	9.0	3519	0.5413	0.894	0.1705	0.1705	None
0.9602	10.0	3910	0.5404	0.895	0.1699	0.1699	None

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu118
Datasets 2.18.0
Tokenizers 0.15.2