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eBay 2022 University Machine Learning Competition

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dlin2028/ebay-umlc

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ebay-umlc

eBay 2022 University Machine Learning Competition team POOPy
https://eval.ai/web/challenges/challenge-page/1733/leaderboard/4120
Finished 9th place

Environment Setup

Install VSCode to run the ipynb files

Update/upgrade packages
sudo apt update && sudo apt upgrade

Download miniconda Installer
Make sure to tell it to init when the installer prompts you
wget https://repo.anaconda.com/miniconda/Miniconda3-py39_4.12.0-Linux-x86_64.sh

After installing miniconda close and reopen your terminal. You may need to run
source ~/.bashrc

Clone the repo
git clone https://github.com/dlin2028/ebay-umlc.git
CD Into the directory
cd ebay-umlc
Create the environment from the environment.yml file (this will take a while)
conda env create -f environment.yml

Running the Full Stack (dataset to output)

Create a new directory ebay-umlc/dataset then paste the dataset .tsv files from the google drive
Make sure you select the poopy environment in VSCode
Generate the trainset by running generate_dataset.ipynb
Generate the word vectors by running word_vector.ipynb
Load the word vectors by running load_word_vector.sh
Train a model using train.sh (make sure to check the gpu-id option is set correctly, do not include it if you don't have a gpu)
Generate a prediction output by running predict.ipynb

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