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Food-Image-Classification-VIT
SeyedAli/Food-Image-Classification-VIT
Food-Image-Classification-VIT is a image classification model from SeyedAli. Use it when you need a label for an image. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- mit
- Model type
- vit
- Access
- Public
- Created
- Sep 13, 2023
- Updated
- Sep 13, 2023
- SHA
- e686f1e5
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
Food-Image-Classification-VIT
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:
- eval_loss: 1.0611
- eval_accuracy: 0.7274
- eval_runtime: 411.0682
- eval_samples_per_second: 61.425
- eval_steps_per_second: 7.68
- epoch: 0.15
- step: 718
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- mit
- Created
- Sep 13, 2023
- Updated
- Sep 13, 2023