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pkr7098/
cifar100-vit-base-patch16-224-in21k

Name: cifar100-vit-base-patch16-224-in21k
Availability: InStock

generated_from_trainer

google/vit-base-patch16-224-in21k

finetune

apache-2.0

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cifar100-vit-base-patch16-224-in21k

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cifar100 dataset. It achieves the following results on the evaluation set:

Loss: 0.2945
Accuracy: 0.926

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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 1337
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3866	1.0	5313	1.0968	0.8747
0.6479	2.0	10626	0.4377	0.9004
0.6092	3.0	15939	0.3439	0.9081
0.4173	4.0	21252	0.3205	0.9169
0.4665	5.0	26565	0.3039	0.9175
0.3944	6.0	31878	0.3082	0.9201
0.303	7.0	37191	0.3011	0.9241
0.6128	8.0	42504	0.2983	0.9261
0.3794	9.0	47817	0.2945	0.926
0.3274	10.0	53130	0.3032	0.9269

Framework versions

Transformers 4.38.0
Pytorch 2.1.2+cu118
Datasets 2.19.1
Tokenizers 0.15.2

pkr7098/cifar100-vit-base-patch16-224-in21k

cifar100-vit-base-patch16-224-in21k

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

pkr7098/
cifar100-vit-base-patch16-224-in21k