README.md

metadata

language:
  - en
license: apache-2.0
task_categories:
  - text-generation
  - fill-mask
tags:
  - code
  - python
  - verl
  - repo-specific-finetuning
pretty_name: Verl Code Corpus (File Holdout Split)
size_categories:
  - n<1K

archit11/verl-code-corpus-track-a-file-split

Repository-specific code corpus extracted from the verl project and split by file for training/evaluation.

What is in this dataset

• Source corpus: data/code_corpus_verl
• Total files: 214
• Train files: 172
• Validation files: 21
• Test files: 21
• File type filter: .py
• Split mode: file (file-level holdout)

Each row has:

• file_name: flattened source file name
• text: full file contents

Training context

This dataset was used for extended pretraining of:

• Model repo: https://huggingface.co/archit11/qwen2.5-coder-3b-verl-track-a-lora
• Base model: /root/.cache/huggingface/hub/models--Qwen--Qwen2.5-Coder-3B/snapshots/09d9bc5d376b0cfa0100a0694ea7de7232525803
• Sequence curriculum: [768, 1024]
• Learning rate: 0.0001
• Batch size: 8

Evaluation from this run:

• Baseline perplexity (val/test): 3.1820 / 2.7764
• Post-training perplexity (val/test): 2.7844 / 2.2379

Load with datasets

from datasets import load_dataset

ds = load_dataset("archit11/verl-code-corpus-track-a-file-split")
print(ds)
print(ds["train"][0]["file_name"])