unlearn_cifar100_resnet-50_neggrad_4_87 – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
unlearn_cifar100_resnet-50_neggrad_4_87

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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: -6.7934
Accuracy: 0.2407
Dt Accuracy: 0.2407
Df Accuracy: 0.233
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: 87
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	-0.5914	0.892	0.2108	0.2108	None
No log	2.0	32	-0.6586	0.8615	0.2575	0.2575	None
No log	3.0	48	-0.7769	0.821	0.3146	0.3146	None
No log	4.0	64	-0.9230	0.7855	0.3599	0.3599	None
No log	5.0	80	-1.1711	0.728	0.4247	0.4247	None
No log	6.0	96	-1.5399	0.6625	0.4851	0.4851	None
No log	7.0	112	-2.0051	0.5945	0.5335	0.5335	None
No log	8.0	128	-2.4841	0.5375	0.5623	0.5623	None
No log	9.0	144	-3.0427	0.4785	0	0	None
No log	10.0	160	-3.6661	0.4235	0	0	None
No log	11.0	176	-4.3184	0.3825	0	0	None
No log	12.0	192	-4.8470	0.3495	0	0	None
No log	13.0	208	-5.4088	0.3195	0	0	None
No log	14.0	224	-5.6832	0.2975	0	0	None
No log	15.0	240	-6.1657	0.2695	0	0	None
No log	16.0	256	-6.4715	0.251	0	0	None
No log	17.0	272	-6.5817	0.2405	0	0	None
No log	18.0	288	-6.6684	0.2325	0	0	None
No log	19.0	304	-6.8003	0.231	0	0	None
No log	20.0	320	-6.7934	0.233	0	0	None

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu118
Datasets 2.18.0
Tokenizers 0.15.2