unlearn-so_cifar10_resnet-50_neggrad_4_13 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn-so_cifar10_resnet-50_neggrad_4_13

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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: -3.0589
Accuracy: 0.6234
Dt Accuracy: 0.6234
Df Accuracy: 0.6235
Unlearn Overall Accuracy: 0.5520
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: 5e-05
train_batch_size: 128
eval_batch_size: 256
seed: 13
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	-0.1157	0.9805	0.2134	0.2134	None
No log	2.0	32	-0.1686	0.962	0.2421	0.2421	None
No log	3.0	48	-0.3309	0.913	0.3120	0.3120	None
No log	4.0	64	-0.7153	0.836	0.4054	0.4054	None
No log	5.0	80	-1.3874	0.7515	0.4836	0.4836	None
No log	6.0	96	-1.9472	0.7035	0.5149	0.5149	None
No log	7.0	112	-2.4520	0.66	0.5395	0.5395	None
No log	8.0	128	-2.7804	0.641	0.5447	0.5447	None
No log	9.0	144	-3.0317	0.628	0.5504	0.5504	None
No log	10.0	160	-3.0589	0.6235	0.5520	0.5520	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2