Implementation of Natural Language Code Search in the project CodeBERT: A Pre-Trained Model for Programming and Natural Languages.

Overview

CodeBERT-Implementation

In this repo we have replicated the paper CodeBERT: A Pre-Trained Model for Programming and Natural Languages.
We are interested in evaluating CodeBERT specifically in Natural language code search. Given a natural language as the input, the objective of code search is to find the most semantically related code from a collection of codes.

This code was implemented on a 64-bit Windows system with 8 GB ram and GeForce GTX 1650 4GB graphics card.

Due to limited compuational power, we have trained and evaluated the model on a smaller data compared to the original data.

Language Training data size Validation data size Test data size for batch_0
Original Our Original Our Original Our
Ruby 97580 500 4417 100 1000000 20000
Go 635653 500 28483 100 1000000 20000
PHP 1047404 500 52029 100 1000000 20000
Python 824342 500 46213 100 1000000 20000
Java 908886 500 30655 100 1000000 20000
Javascript 247773 500 16505 100 1000000 20000

Compared to the code in original repo, code in this repo can be implemented directly in Windows system without any hindrance. We have already provided a subset of pre-processed data for batch_0 (shown in table under Testing data size) in ./data/codesearch/test/

Fine tuning pretrained model CodeBERT on individual languages

lang = go
cd CodeBERT-Implementation
! python run_classifier.py --model_type roberta --task_name codesearch --do_train --do_eval --eval_all_checkpoints --train_file train_short.txt --dev_file valid_short.txt --max_seq_length 50 --per_gpu_train_batch_size 8 --per_gpu_eval_batch_size 8 --learning_rate 1e-5 --num_train_epochs 1 --gradient_accumulation_steps 1 --overwrite_output_dir --data_dir CodeBERT-Implementation/data/codesearch/train_valid/$lang/ --output_dir ./models/$lang/ --model_name_or_path microsoft/codebert-base

Inference and Evaluation

lang = go
idx = 0
! python run_classifier.py --model_type roberta --model_name_or_path microsoft/codebert-base --task_name codesearch --do_predict --output_dir CodeBERT-Implementation/data/models/$lang --data_dir CodeBERT-Implementation/data/codesearch/test/$lang/ --max_seq_length 50 --per_gpu_train_batch_size 8 --per_gpu_eval_batch_size 8 --learning_rate 1e-5 --num_train_epochs 1 --test_file batch_short_${idx}.txt --pred_model_dir ./models/ruby/checkpoint-best/ --test_result_dir ./results/$lang/${idx}_batch_result.txt
! python mrr.py

The Mean Evaluation Rank (MER), the evaluation mteric, for the subset of data is given as follows:

Language MER
Ruby 0.0037
Go 0.0034
PHP 0.0044
Python 0.0052
Java 0.0033
Java script 0.0054

The accuracy is way less than what is reported in the paper. However, the purpose of this repo is to provide the user, ready to implement data of CodeBERT without any heavy downloads. We have also included the prediction results in this repo corresponding to the test data.

Owner
Tanuj Sur
Student at Chennai Mathematical Institute | Research Intern at TCS Research and Innovation Labs
Tanuj Sur
Unsupervised text tokenizer for Neural Network-based text generation.

SentencePiece SentencePiece is an unsupervised text tokenizer and detokenizer mainly for Neural Network-based text generation systems where the vocabu

Google 6.4k Jan 01, 2023
This repo contains simple to use, pretrained/training-less models for speaker diarization.

PyDiar This repo contains simple to use, pretrained/training-less models for speaker diarization. Supported Models Binary Key Speaker Modeling Based o

12 Jan 20, 2022
Natural Language Processing Specialization

Natural Language Processing Specialization In this folder, Natural Language Processing Specialization projects and notes can be found. WHAT I LEARNED

Kaan BOKE 3 Oct 06, 2022
The code for the Subformer, from the EMNLP 2021 Findings paper: "Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers", by Machel Reid, Edison Marrese-Taylor, and Yutaka Matsuo

Subformer This repository contains the code for the Subformer. To help overcome this we propose the Subformer, allowing us to retain performance while

Machel Reid 10 Dec 27, 2022
Coreference resolution for English, French, German and Polish, optimised for limited training data and easily extensible for further languages

Coreferee Author: Richard Paul Hudson, Explosion AI 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 French 1.2.3 German 1.2

Explosion 70 Dec 12, 2022
Kestrel Threat Hunting Language

Kestrel Threat Hunting Language What is Kestrel? Why we need it? How to hunt with XDR support? What is the science behind it? You can find all the ans

Open Cybersecurity Alliance 201 Dec 16, 2022
Chinese version of GPT2 training code, using BERT tokenizer.

GPT2-Chinese Description Chinese version of GPT2 training code, using BERT tokenizer or BPE tokenizer. It is based on the extremely awesome repository

Zeyao Du 5.6k Jan 04, 2023
This repository contains data used in the NAACL 2021 Paper - Proteno: Text Normalization with Limited Data for Fast Deployment in Text to Speech Systems

Proteno This is the data release associated with the corresponding NAACL 2021 Paper - Proteno: Text Normalization with Limited Data for Fast Deploymen

37 Dec 04, 2022
Conversational-AI-ChatBot - Intelligent ChatBot built with Microsoft's DialoGPT transformer to make conversations with human users!

Conversational AI ChatBot Intelligent ChatBot built with Microsoft's DialoGPT transformer to make conversations with human users! In this project? Thi

Rajkumar Lakshmanamoorthy 6 Nov 30, 2022
Treemap visualisation of Maya scene files

Ever wondered which nodes are responsible for that 600 mb+ Maya scene file? Features Fast, resizable UI Parsing at 50 mb/sec Dependency-free, single-f

Marcus Ottosson 76 Nov 12, 2022
Natural Language Processing at EDHEC, 2022

Natural Language Processing Here you will find the teaching materials for the "Natural Language Processing" course at EDHEC Business School, 2022 What

1 Feb 04, 2022
This code extends the neural style transfer image processing technique to video by generating smooth transitions between several reference style images

Neural Style Transfer Transition Video Processing By Brycen Westgarth and Tristan Jogminas Description This code extends the neural style transfer ima

Brycen Westgarth 110 Jan 07, 2023
The code from the whylogs workshop in DataTalks.Club on 29 March 2022

whylogs Workshop The code from the whylogs workshop in DataTalks.Club on 29 March 2022 whylogs - The open source standard for data logging (Don't forg

DataTalksClub 12 Sep 05, 2022
A list of NLP(Natural Language Processing) tutorials

NLP Tutorial A list of NLP(Natural Language Processing) tutorials built on PyTorch. Table of Contents A step-by-step tutorial on how to implement and

Allen Lee 1.3k Dec 25, 2022
Deduplication is the task to combine different representations of the same real world entity.

Deduplication is the task to combine different representations of the same real world entity. This package implements deduplication using active learning. Active learning allows for rapid training wi

63 Nov 17, 2022
使用Mask LM预训练任务来预训练Bert模型。训练垂直领域语料的模型表征,提升下游任务的表现。

Pretrain_Bert_with_MaskLM Info 使用Mask LM预训练任务来预训练Bert模型。 基于pytorch框架,训练关于垂直领域语料的预训练语言模型,目的是提升下游任务的表现。 Pretraining Task Mask Language Model,简称Mask LM,即

Desmond Ng 24 Dec 10, 2022
Code release for NeX: Real-time View Synthesis with Neural Basis Expansion

NeX: Real-time View Synthesis with Neural Basis Expansion Project Page | Video | Paper | COLAB | Shiny Dataset We present NeX, a new approach to novel

537 Jan 05, 2023
Generating new names based on trends in data using GPT2 (Transformer network)

MLOpsNameGenerator Overall Goal The goal of the project is to develop a model that is capable of creating Pokémon names based on its description, usin

Gustav Lang Moesmand 2 Jan 10, 2022
A fast, efficient universal vector embedding utility package.

Magnitude: a fast, simple vector embedding utility library A feature-packed Python package and vector storage file format for utilizing vector embeddi

Plasticity 1.5k Jan 02, 2023
Estimation of the CEFR complexity score of a given word, sentence or text.

NLP-Swedish … allows to estimate CEFR (Common European Framework of References) complexity score of a given word, sentence or text. CEFR scores come f

3 Apr 30, 2022