README.md

metadata

pretty_name: BTZSC Leaderboard Results
license: mit
tags:
  - leaderboard
  - text-classification
  - zero-shot
  - evaluation
language:
  - en

BTZSC Results

This repository stores model submissions for the BTZSC leaderboard.

BTZSC: A Benchmark for Zero-Shot Text Classification across Cross-Encoders, Embedding Models, Rerankers and LLMs.

• Paper: https://openreview.net/forum?id=IxMryAz2p3
• Eval harness: https://github.com/IliasAarab/btzsc
• Leaderboard Space: https://huggingface.co/spaces/btzsc/btzsc-leaderboard

Benchmark summary:

• 22 English single-label datasets
• 4 task families: sentiment, topic, intent, emotion
• Strict zero-shot protocol (no BTZSC-label training/tuning)
• Primary metric: macro-F1

What this repo contains

• One JSON file per model evaluation run in results/<model_type>/<model-name>.json
• Reproducibility metadata (BTZSC version, commit, precision, batch size)
• Full per-dataset metrics for all 22 BTZSC datasets

Schema

Each submission follows schema version 1.0 with:

• model: model id, type, parameter count, revision
• evaluation: harness versioning and runtime metadata
• results.overall: averaged macro F1 / accuracy / macro precision / macro recall
• results.by_task: sentiment/topic/intent/emotion aggregates
• results.by_dataset: per-dataset metric blocks

Contributing results

Destination path format:

• results/<model_type>/<model-name>.json

Recommended flow:

1. Export with the official harness (btzsc evaluate ... --output-json ...).
2. Validate locally (python validate.py results/<model_type>/<model-name>.json).
3. Add your file at the required path.
4. Submit by one of these methods:

• Web UI upload on Hugging Face (no clone required)
• Git workflow (direct push if you have write access, otherwise fork + PR)
• API workflow via huggingface_hub with create_pr=True (PR-based)

In short: add means placing the JSON at the correct path; submit means publishing that change to this remote repo.

See SUBMISSION.md for full requirements and review checks.

PRs adding result files are validated in CI with validate.py.