DianJin/DianJin-Fin-PRM-Data
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---
language:
- zh
license: apache-2.0
size_categories:
- 1K<n<10K
task_categories:
- question-answering
- text-generation
tags:
- finance
- process-reward-model
- PRM
- Chinese
- evaluation
dataset_info:
features:
- name: 名称
dtype: string
- name: 科目
dtype: string
- name: 章节
dtype: string
- name: task
dtype: string
- name: question
dtype: string
- name: choices
dtype: string
- name: answer
dtype: string
- name: analysis
dtype: string
- name: analysis_length
dtype: int64
- name: trace
dtype: string
- name: final_answer
dtype: string
- name: knowlegde_coverage_response
dtype: string
- name: knowledge_coverage_score
dtype: float64
- name: coverage_knowledge_points
dtype: string
- name: importance_labels
dtype: string
- name: analysis_knowledge
dtype: string
- name: knowledge_accuracy
dtype: string
- name: quality_score
dtype: string
- name: model_answer
dtype: string
- name: accuracy_score
dtype: string
- name: step_scores
dtype: string
- name: step_labels
dtype: string
- name: trajectory_label
dtype: int64
splits:
- name: train
num_examples: 4969
---
# DianJin-Fin-PRM Dataset
## Overview
DianJin-Fin-PRM is a Chinese financial domain **Process Reward Model (PRM)** training dataset. It contains 4,969 samples of financial exam questions with step-by-step reasoning traces and multi-dimensional quality annotations.
## Dataset Structure
| Field | Type | Description |
|---|---|---|
| `名称` | string | Exam name (e.g., 初级经济师) |
| `科目` | string | Subject (e.g., 金融实务) |
| `章节` | string | Chapter |
| `task` | string | Question type (e.g., 单项选择题) |
| `question` | string | Question text |
| `choices` | string | Answer choices (JSON dict) |
| `answer` | string | Ground truth answer |
| `analysis` | string | Reference analysis |
| `analysis_length` | int | Length of reference analysis |
| `trace` | string | Step-by-step reasoning trace |
| `final_answer` | string | Model's final answer with reasoning |
| `knowlegde_coverage_response` | string | Knowledge coverage evaluation response |
| `knowledge_coverage_score` | float | Knowledge coverage score (0-1) |
| `coverage_knowledge_points` | string | Covered knowledge points (JSON list) |
| `importance_labels` | string | Step importance labels (JSON list) |
| `analysis_knowledge` | string | Knowledge points from analysis (JSON list) |
| `knowledge_accuracy` | string | Per-step knowledge accuracy (JSON list) |
| `quality_score` | string | Per-step quality scores (JSON list of dicts with logical_soundness, step_correctness, target_progression) |
| `model_answer` | string | Model's extracted answer |
| `accuracy_score` | string | Per-step accuracy scores (JSON list) |
| `step_scores` | string | Aggregated per-step scores (JSON list) |
| `step_labels` | string | Per-step binary labels (JSON list) |
| `trajectory_label` | int | Overall trajectory label (1=correct, 0=incorrect) |
## Usage
```python
from datasets import load_dataset
dataset = load_dataset("DianJin/DianJin-Fin-PRM-Data")
```
## Citation
If you use this dataset, please cite:
```bibtex
@misc{dianjin-fin-prm,
title={DianJin-Fin-PRM: A Chinese Financial Process Reward Model Dataset},
author={DianJin Team},
year={2025}
}
```
## License
Apache License 2.0
提供机构：
DianJin
