unlearn_cifar10_resnet-50_bad_teaching_2_42 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar10_resnet-50_bad_teaching_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 cifar10 dataset. It achieves the following results on the evaluation set:

Loss: 0.2368
Accuracy: 0.9504
Dt Accuracy: 0.9504
Df Accuracy: 0.961
Unlearn Overall Accuracy: 0.2436
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
No log	1.0	16	0.1279	0.983	0.2094	0.2094	None
No log	2.0	32	0.1410	0.979	0.2157	0.2157	None
No log	3.0	48	0.1546	0.981	0.2125	0.2125	None
No log	4.0	64	0.1752	0.977	0.2188	0.2188	None
No log	5.0	80	0.1980	0.973	0.2251	0.2251	None
No log	6.0	96	0.2073	0.968	0.2328	0.2328	None
No log	7.0	112	0.2380	0.96	0.2451	0.2451	None
No log	8.0	128	0.2355	0.961	0.2436	0.2436	None
No log	9.0	144	0.2476	0.963	0.2404	0.2404	None
No log	10.0	160	0.2368	0.961	0.2436	0.2436	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2