skincare-detection – AI Model by tuphamdf | AlphaNeural AI

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tuphamdf/
skincare-detection

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image-classification

generated_from_trainer

google/vit-base-patch16-224-in21k

autotrain_compatible

endpoints_compatible

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skincare-detection

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4840
Accuracy: 0.8648

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: 0.0002
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: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3961	0.99	61	0.5629	0.7725
0.4982	2.0	123	0.3991	0.8435
0.3563	2.99	184	0.4330	0.8272
0.2314	4.0	246	0.3969	0.8554
0.1815	4.99	307	0.4492	0.8435
0.1332	6.0	369	0.4474	0.8580
0.0869	6.99	430	0.4520	0.8631
0.0844	8.0	492	0.4469	0.8640
0.0681	8.99	553	0.4533	0.8717
0.0574	10.0	615	0.4952	0.8597
0.0477	10.99	676	0.4772	0.8674
0.0454	11.9	732	0.4840	0.8648

Framework versions

Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.17.1
Tokenizers 0.15.2