CCT-Organism-7x244

Model Card: CCT Model for Organism Classification

Model Overview

This model is a Convolutional Contrastive Transformer (CCT) architecture trained on a dataset containing images of both animals and plants. The dataset includes all the animal and plant classes from the ImageNet1k dataset. The model is designed for classifying images into the Organism classes, which cover a broad range of organisms.

Training Details

• Dataset: A custom dataset containing images from the animal and plant classes of the ImageNet1k dataset.
• Task: Organism classification, where the model categorizes images into specific organism classes.
• Model Architecture: Convolutional Contrastive Transformer (CCT).
• Training Parameters: The model was trained using the parameters defined in the args.yml file that was uploaded.

Available Checkpoints

The following model checkpoints are provided:

1. model_best_sd.pth:

   • This checkpoint can be directly used for classification tasks.

2. model_best.pth.tar:

   • This checkpoint contains parameters from previous training iterations and can be used for further fine-tuning or continued training.

How to Use

1. For Classification: Use the pre-trained model available in model_best_sd.pth to directly perform image classification on the Organism classes.

2. For Fine-Tuning: If you wish to continue training the model with your own dataset or further fine-tune it, you can start from the checkpoint model_best.pth.tar. This checkpoint includes the parameters from the previous training and allows for continued training.

Usage Instructions

# To use the model for classification:
python classify.py --model model_best_sd.pth --input <your_image_path> --output <output_path>

# To continue training:
python train.py --model model_best.pth.tar --args args.yml