library_name: transformers
tags:
- electronics
- sciences
- components
license: apache-2.0
datasets:
- qipchip31/electronic_components
language:
- en
metrics:
- accuracy
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Model Details
Model Description
The fine-tuned Vision Transformer (ViT) model, initialized from google/vit-base-patch16-224 and named electronic-components-model, is specialized for classifying electronic components such as resistors, capacitors, inductors, and transistors. Initially pretrained on broader datasets, the fine-tuning process adjusts model parameters specifically for this custom dataset. This adaptation enhances the electronic-components-model's ability to accurately identify and classify intricate visual features unique to electronic components, improving its efficacy in practical applications requiring automated component recognition based on visual inputs.
- Developed by: Chirag Pradhan
- Funded by [optional]: Fatima Al-Fihri Predoctoral Fellowship
- Shared by [optional]: Chirag Pradhan
- Model type: Vision Transformer (ViT) for image classification
- Language(s) (NLP): Not applicable (Image classification)
- License: Apache License 2.0
- Finetuned from model [optional]: google/vit-base-patch16-224
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