my_awesome_food_model

Full notebook :

https://github.com/MustafaAlahmid/hugging_face_models/blob/main/Vit-classifier_food_dataset.ipynb

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license: apache-2.0 tags:

• generated_from_trainer datasets:
• food101 metrics:
• accuracy model-index:
• name: my_awesome_food_model results:
  • task: name: Image Classification type: image-classification dataset: name: food101 type: food101 config: default split: train[:1000] args: default metrics:
    • name: Accuracy type: accuracy value: 0.985

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my_awesome_food_model

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: 1.2335
• Accuracy: 0.985

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• 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

Framework versions

• Transformers 4.26.0
• Pytorch 1.13.1+cu116
• Datasets 2.9.0
• Tokenizers 0.13.2