vit_101

justinsiow/vit_101

vit_101 is a image classification model from justinsiow. 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: Oct 24, 2023
Updated: Oct 24, 2023
SHA: 4a3c7ca1

Datasets

food101

Model card

From the Hugging Face model README

vit_101

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the food101 dataset. It achieves the following results on the evaluation set:

Loss: 1.6267
Accuracy: 0.88

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
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.7266	0.99	62	2.5317	0.814
1.8315	2.0	125	1.7931	0.864
1.5845	2.98	186	1.6267	0.88

Framework versions

Transformers 4.27.2
Pytorch 2.1.0.dev20230428
Datasets 2.10.1
Tokenizers 0.13.2

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Oct 24, 2023
Updated: Oct 24, 2023