SimCLR Implementation

Paper link: https://arxiv.org/pdf/2002.05709.pdf

This repository contains an implementation of SimCLR (Simple Framework for Contrastive Learning of Visual Representations) done as a part of my Deep Learning Project. SimCLR is a self-supervised learning framework that uses contrastive learning to learn useful visual representations without labeled data.

Installation

1. Clone the repository:

   git clone https://github.com/harini-si/SimCLR.git
   cd SimCLR

2. Install the required dependencies:

   pip install -r requirements.txt

Usage

To train the SimCLR model, run:

cd src
python main_imagenet.py  --epochs 100 --batch_size 256

To evaluate, run :

cd model
python evaluator.py