unlearn_cifar100_resnet-50_neggrad_4_42 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar100_resnet-50_neggrad_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 cifar100 dataset. It achieves the following results on the evaluation set:

Loss: -7.5901
Accuracy: 0.1781
Dt Accuracy: 0.1781
Df Accuracy: 0.175
Unlearn Overall Accuracy: 0
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: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	16	-0.5943	0.8955	0.2053	0.2053	None
No log	2.0	32	-0.6878	0.851	0.2729	0.2729	None
No log	3.0	48	-0.8240	0.8135	0.3244	0.3244	None
No log	4.0	64	-1.0586	0.7495	0.4021	0.4021	None
No log	5.0	80	-1.3593	0.686	0.4653	0.4653	None
No log	6.0	96	-1.7478	0.6355	0.5028	0.5028	None
No log	7.0	112	-2.3184	0.5545	0.5506	0.5506	None
No log	8.0	128	-2.8628	0.489	0	0	None
No log	9.0	144	-3.5199	0.4245	0	0	None
No log	10.0	160	-4.2017	0.3815	0	0	None
No log	11.0	176	-4.8407	0.3315	0	0	None
No log	12.0	192	-5.3785	0.2875	0	0	None
No log	13.0	208	-5.8581	0.258	0	0	None
No log	14.0	224	-6.4548	0.235	0	0	None
No log	15.0	240	-6.7097	0.2175	0	0	None
No log	16.0	256	-6.9746	0.1955	0	0	None
No log	17.0	272	-7.1407	0.1885	0	0	None
No log	18.0	288	-7.4623	0.182	0	0	None
No log	19.0	304	-7.4725	0.1775	0	0	None
No log	20.0	320	-7.5901	0.175	0	0	None

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu118
Datasets 2.18.0
Tokenizers 0.15.2