size_categories:n<1K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
dataset_info:
  features:
  - name: source
    dtype: string
  - name: instruction
    dtype: string
  - name: messages
    list:
    - name: content
      dtype: string
    - name: role
      dtype: string
  - name: followup_question
    dtype: string
  - name: model
    dtype: string
  splits:
  - name: train_sft
    num_bytes: 954797
    num_examples: 238
  download_size: 548182
  dataset_size: 954797
configs:
- config_name: default
  data_files:
  - split: train_sft
    path: data/train_sft-*
size_categories:
- n<1K
---

# Ruozhiba English Data

Based on the findings from [COIG-CQIA](https://arxiv.org/html/2403.18058v1), Ruozhiba data is a high-quality instruction tuning dataset that can greatly improve supervised fine-tuning models' performance.
We translated the 240 instructions in Ruozhiba from Chinese to English. 
We filtered out and modified some instructions are language/cultural related.
Some Chinese instructions are kept to maintain their original meaning.
Finally, we re-generate the response using `gpt-4-turbo` and add one additional turn to improve robustness.

## MT-Bench

We use GPT-4-0125-preview as Judge. On MT-Bench, [ruozhiba_en](https://huggingface.co/datasets/qywu/ruozhiba_en) data has achieved comparable performance compared to [ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k) dataset.

| Model                                      | Total | Coding | Extraction | Humanities | Math | Reasoning | Roleplay | STEM | Writing |
|--------------------------------------------|-------|--------|------------|------------|------|-----------|----------|------|---------|
| alignment-handbook/zephyr-7b-sft-full      | 5.6   | 3.95   | 6.75       | 7.5        | 3.1  | 4.05      | 6.15     | 6.1  | 7.2     |
| zephyr-7b-sft-ruozhiba                     | 5.88  | 3.75    | 6.45        | 8.11       | 2.7  | 4.2       | 7.4    | 7.4  | 7.15    |