unlearn_cifar10_resnet-50_salun_10_42 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar10_resnet-50_salun_10_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: 0.2012
Accuracy: 0.9658
Dt Accuracy: 0.9658
Df Accuracy: 0.8946
Unlearn Overall Accuracy: 0.3407
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	0.1930	0.8818	0.3578	0.3578	None
0.753	2.0	782	0.2038	0.8844	0.3543	0.3543	None
0.6508	3.0	1173	0.2003	0.8874	0.3505	0.3505	None
0.6353	4.0	1564	0.2144	0.8884	0.3490	0.3490	None
0.6353	5.0	1955	0.2010	0.8992	0.3343	0.3343	None
0.6213	6.0	2346	0.2095	0.895	0.3399	0.3399	None
0.6126	7.0	2737	0.2060	0.8974	0.3369	0.3369	None
0.6098	8.0	3128	0.1985	0.8884	0.3491	0.3491	None
0.6029	9.0	3519	0.2074	0.8908	0.3459	0.3459	None
0.6029	10.0	3910	0.2012	0.8946	0.3407	0.3407	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2