|
|
| --- |
| pretty_name: YCbench |
| dataset_name: ycbench |
| language: |
| - en |
| license: mit |
| tags: |
| - finance |
| - startups |
| - ycombinator |
| - benchmarking |
| - tabular |
| - prediction |
| - venture-capital |
| task_categories: |
| - tabular-classification |
| - text-classification |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: startups |
| data_files: yc_w26_startups.csv |
| - config_name: traction |
| data_files: yc_w26_traction.csv |
| - config_name: scores |
| data_files: yc_w26_pre_demo_scores.csv |
| - config_name: mentions |
| data_files: yc_mentions.csv |
| - config_name: mentions_early |
| data_files: yc_mentions_early.csv |
| --- |
| |
| # YCbench |
|
|
| **A live benchmark dataset for forecasting startup outperformance in Y Combinator batches.** |
|
|
| This dataset was introduced in the paper: |
| **["YC Bench: a Live Benchmark for Forecasting Startup Outperformance in Y Combinator Batches"](https://huggingface.co/papers/2604.02378)** by Mostapha Benhenda. |
|
|
| ## Dataset Overview |
|
|
| YCbench provides structured public signals for Y Combinator startups (focused on the **W26** batch of 196 companies). It enables rapid evaluation of models that predict which startups will **outperform their batch peers** in the short term (until Demo Day). |
|
|
| Performance is measured using a **Pre-Demo Day Score** that combines traction signals and web visibility. |
|
|
| ### Available Configurations |
|
|
| | Config | File | Description | |
| |-----------------|-------------------------------|------------------------------------------| |
| | `startups` | `yc_w26_startups.csv` | Basic startup information | |
| | `traction` | `yc_w26_traction.csv` | Traction metrics | |
| | `scores` | `yc_w26_pre_demo_scores.csv` | Pre-demo day scores + velocity | |
| | `mentions` | `yc_mentions.csv` | Google/web mention counts | |
| | `mentions_early`| `yc_mentions_early.csv` | Early-stage mention data | |
|
|
| ## Quick Load |
|
|
| ```python |
| from datasets import load_dataset |
| |
| # Load specific parts |
| startups = load_dataset("benstaf/ycbench", "startups") |
| scores = load_dataset("benstaf/ycbench", "scores") |
| mentions = load_dataset("benstaf/ycbench", "mentions") |
| ``` |
|
|
| Or with pandas (simple way): |
| ``` |
| import pandas as pd |
| df = pd.read_csv("hf://datasets/benstaf/ycbench/yc_w26_pre_demo_scores.csv") |
| ``` |
|
|
| ## Links |
|
|
| - **Paper**: [arXiv 2604.02378](https://huggingface.co/papers/2604.02378) |
| - **Live Benchmark**: [ycbench.com](https://ycbench.com/) |
| - **GitHub**: [benstaf/ycbench](https://github.com/benstaf/ycbench) |
|
|
