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--- |
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tags: |
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- autotrain |
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- vision |
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- image-classification |
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datasets: |
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- fsuarez/autotrain-data-autotrain-simple-classifierv2 |
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widget: |
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg |
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example_title: Tiger |
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg |
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example_title: Teapot |
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg |
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example_title: Palace |
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co2_eq_emissions: |
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emissions: 1.0491199369635873 |
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--- |
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# Model Description: |
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This model embodies a Vision Transformer (ViT) architecture tailored for image classification tasks. It's honed to accurately categorize |
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images into three specific classes: Button, RadioButton, and CheckBox. |
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# Training Data: |
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It's trained on a dataset comprising images from the three classes—Button, RadioButton, and CheckBox—enabling it to adeptly recognize and classify these distinct visual elements. |
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# Model Trained Using AutoTrain |
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- Problem type: Multi-class Classification |
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- Model ID: 84935142669 |
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- CO2 Emissions (in grams): 1.0491 |
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## Validation Metrics |
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- Loss: 0.111 |
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- Accuracy: 0.969 |
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- Macro F1: 0.935 |
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- Micro F1: 0.969 |
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- Weighted F1: 0.969 |
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- Macro Precision: 0.934 |
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- Micro Precision: 0.969 |
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- Weighted Precision: 0.970 |
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- Macro Recall: 0.939 |
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- Micro Recall: 0.969 |
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- Weighted Recall: 0.969 |
