vit-base-patch16-224-finetuned-foveated-features-v2

annazhong/vit-base-patch16-224-finetuned-foveated-features-v2

vit-base-patch16-224-finetuned-foveated-features-v2 is a image classification model from annazhong. 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: Jul 25, 2023
Updated: Jul 25, 2023
SHA: 542832ec

Base models

google/vit-base-patch16-224

Model card

From the Hugging Face model README

vit-base-patch16-224-finetuned-foveated-features-v2

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: 1.9396
Accuracy: 0.24

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: 150
eval_batch_size: 150
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 600
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
No log	1.0	1	1.9396	0.24
No log	2.0	3	1.9830	0.12

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.0
Tokenizers 0.13.3

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Jul 25, 2023
Updated: Jul 25, 2023