unlearn_cifar10_resnet-50_salun_8_42 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar10_resnet-50_salun_8_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: 0.1823
Accuracy: 0.9648
Dt Accuracy: 0.9648
Df Accuracy: 0.887
Unlearn Overall Accuracy: 0.3510
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	391	0.1770	0.8912	0.3451	0.3451	None
0.6926	2.0	782	0.1856	0.8892	0.3479	0.3479	None
0.6055	3.0	1173	0.1789	0.887	0.3510	0.3510	None
0.5939	4.0	1564	0.1893	0.8918	0.3445	0.3445	None
0.5939	5.0	1955	0.1926	0.8885	0.3489	0.3489	None
0.5712	6.0	2346	0.1883	0.895	0.3402	0.3402	None
0.5655	7.0	2737	0.1900	0.891	0.3456	0.3456	None
0.5622	8.0	3128	0.1780	0.8908	0.3459	0.3459	None
0.5572	9.0	3519	0.1866	0.9067	0.3238	0.3238	None
0.5572	10.0	3910	0.1823	0.887	0.3510	0.3510	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2