vit-base-patch16-224-v21 – AI Model by pphildan | AlphaNeural AI

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pphildan/
vit-base-patch16-224-v21

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image-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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vit-base-patch16-224-v21

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

Loss: 0.0347
Accuracy: 0.99

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: 0.0005
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2951	1.0	190	0.1895	0.9333
0.2013	2.0	380	0.0813	0.9726
0.1935	3.0	570	0.0902	0.9681
0.1858	4.0	760	0.0916	0.9674
0.118	5.0	950	0.0481	0.9833
0.0834	6.0	1140	0.0578	0.9841
0.0986	7.0	1330	0.0418	0.9870
0.0737	8.0	1520	0.0347	0.99

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu118
Tokenizers 0.13.3