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license: apache-2.0 |
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datasets: |
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- bharat-raghunathan/indian-foods-dataset |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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# Indian Food Classification with Vision Transformer (ViT) |
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## Overview |
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This model is a fine-tuned Vision Transformer (ViT) for the task of classifying images of Indian foods. The model was trained on the [Indian Foods Dataset](https://huggingface.co/datasets/bharat-raghunathan/indian-foods-dataset) from Hugging Face Datasets. |
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## Dataset |
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The Indian Foods Dataset contains 4,770 images across 15 different classes of popular Indian dishes. The dataset is split into: |
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- Training: 3,047 images |
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- Validation: 762 images |
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- Testing: 961 images |
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## Model |
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The base model used is the vision transformer (google/vit-base-patch16-224-in21k). The model was fine-tuned on the Indian Foods Dataset for 10 epochs using the AdamW optimizer with a learning rate of 2e-4. |
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## Evaluation |
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The model was evaluated on the test set and achieved the following metrics: |
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- Accuracy: 0.9667 |
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- Precision: 0.9670 |
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- Recall: 0.9667 |
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## Usage |
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You can use this pre-trained model directly from Hugging Face |
