unlearn_cifar10_resnet-50_bad_teaching_4_42 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar10_resnet-50_bad_teaching_4_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: 0.9525
Accuracy: 0.8914
Dt Accuracy: 0.8914
Df Accuracy: 0.897
Unlearn Overall Accuracy: 0.3329
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	32	0.1667	0.972	0.2266	0.2266	None
No log	2.0	64	0.2031	0.9675	0.2336	0.2336	None
No log	3.0	96	0.2669	0.96	0.245	0.245	None
No log	4.0	128	0.3595	0.946	0.2658	0.2658	None
No log	5.0	160	0.5510	0.929	0.2899	0.2899	None
No log	6.0	192	0.6281	0.9235	0.2975	0.2975	None
No log	7.0	224	0.7606	0.9165	0.3069	0.3069	None
No log	8.0	256	0.8358	0.9035	0.3243	0.3243	None
No log	9.0	288	0.9320	0.8985	0.3309	0.3309	None
No log	10.0	320	0.9525	0.897	0.3329	0.3329	None

Framework versions

Transformers 4.37.2
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2