unlearn-so_cifar100_resnet-50_neggrad_2_100 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn-so_cifar100_resnet-50_neggrad_2_100

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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 cifar100 dataset. It achieves the following results on the evaluation set:

Loss: -1.1130
Accuracy: 0.7225
Dt Accuracy: 0.7225
Df Accuracy: 0.702
Unlearn Overall Accuracy: 0.4576
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: 100
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	8	-0.5790	0.9	0.1981	0.1981	None
No log	2.0	16	-0.6284	0.869	0.2464	0.2464	None
No log	3.0	24	-0.6941	0.834	0.2975	0.2975	None
No log	4.0	32	-0.7636	0.808	0.3330	0.3330	None
No log	5.0	40	-0.8454	0.775	0.3755	0.3755	None
No log	6.0	48	-0.9352	0.75	0.4054	0.4054	None
No log	7.0	56	-1.0095	0.73	0.4279	0.4279	None
No log	8.0	64	-1.0687	0.715	0.4439	0.4439	None
No log	9.0	72	-1.1105	0.705	0.4543	0.4543	None
No log	10.0	80	-1.1130	0.702	0.4576	0.4576	None

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu118
Datasets 2.19.0
Tokenizers 0.15.2