NLP Classifier

Introduction

This project trains a bert model on any NLP classifcation model. And uses the model in make predictions on new data using batch_inference.py. This architecture can be easily extended to cover a lot more models.

Installation

Set up

• $ https://github.com/abdullahtarek/nlp_classifier.git
• $ cd nlp_classifier.git
• Move the train.csv and test.csv in the data folder

Python

• $ pip install -r requirements.txt
• $ Copy the training or testing dataset in the "data" folder
• $ python training.py or $ python batch_inference.py

Docker

• $ docker build . -t nlp_classifier
• $ docker run -it -v $DATA_FOLDER:/app/data -v $LOCAL_SAVED_MODEL_FOLDER:/app/saved_models nlp_classifier python batch_inference.py or python training.py

Extra options

Manging Configurations

• All configurations are in the conf folder where you can change the data path, model path, etc.
• You can also provide the configuration flag while running the script. You can write --help after the python command to see which configs you can change. Example: python3 batch_inference.py --help.