Skip to content

manhph2211/CLS-Template

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

29 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

IR-Project

Introduction 😄

In this project, I provided an simple end-to-end implemetation for training, evaluating and monitoring a stardard classifier which is considered as a common template and easy-to-use for AI newbies. I did apply several techniques such as Expotential Moving Average (EMA), Label Smoothing, Modern Optimizer, K-Fold cross-validation, random-augmentations ... traking logs, hyperparameters ... with comet ML tool.

Packages

comet_ml
timm
opencv-python
torch
torchvision

Data

Here we want to test our method with 5-Fold Cross-Validation. We just need to put FOLD_i into folder ./data.

Usage

First, set the value of ROOT in config file config.yml so that you can train the case(Fold_i) you want.

Then, for experimental logging info, I used framework comet_ml. We need to create a file called experiment_apikey.txt. This file will just contain your api_key that the main website of comet_ml provides you when you create your own account.

For create data form for dataset, we need config files. Here just run python3 utils.py

For training, we run python3 main.py

Releases

No releases published

Packages

No packages published