MaskedForehead_image_parts_df_VIT

thenewsupercell/MaskedForehead_image_parts_df_VIT

MaskedForehead_image_parts_df_VIT is a image classification model from thenewsupercell. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Image Classification
Library: transformers
License: apache-2.0
Model type: vit
Access: Public
Created: Apr 15, 2025
Updated: Apr 15, 2025
SHA: 426dae32

Base models

google/vit-base-patch16-224-in21k

Model card

From the Hugging Face model README

MaskedForehead_image_parts_df_VIT

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

Loss: 0.0184
Accuracy: 0.9965

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: 16
eval_batch_size: 16
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0347	1.0	5252	0.0299	0.9908
0.0095	2.0	10504	0.0208	0.9944
0.0004	3.0	15756	0.0196	0.9955
0.0102	4.0	21008	0.0184	0.9965

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Apr 15, 2025
Updated: Apr 15, 2025