|
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--- |
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dataset_info: |
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- config_name: agricultural_procedural_reasoning |
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features: |
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|
- name: id |
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dtype: string |
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|
- name: question |
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|
dtype: string |
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|
- name: options |
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|
struct: |
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|
- name: default |
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|
sequence: string |
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|
- name: diff_1 |
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|
sequence: string |
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|
- name: diff_2 |
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|
sequence: string |
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|
- name: diff_3 |
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sequence: string |
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|
- name: diff_4 |
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|
sequence: string |
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|
- name: diff_5 |
|
|
sequence: string |
|
|
- name: answer |
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|
dtype: string |
|
|
- name: accepted_answers |
|
|
sequence: string |
|
|
- name: category |
|
|
dtype: string |
|
|
- name: task_type |
|
|
dtype: string |
|
|
- name: question_type |
|
|
sequence: string |
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|
- name: metadata |
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|
dtype: string |
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|
splits: |
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- name: wikihow_arrange |
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|
num_bytes: 658484 |
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|
num_examples: 557 |
|
|
- name: wikihow_missing |
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|
num_bytes: 604774 |
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num_examples: 526 |
|
|
- name: wikihow_next |
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|
num_bytes: 602898 |
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|
num_examples: 538 |
|
|
- name: wikihow_all |
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|
num_bytes: 669007 |
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num_examples: 520 |
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|
download_size: 1052251 |
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dataset_size: 2535163 |
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- config_name: agricultural_scientific_knowledge |
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features: |
|
|
- name: id |
|
|
dtype: string |
|
|
- name: question |
|
|
dtype: string |
|
|
- name: options |
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|
struct: |
|
|
- name: default |
|
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sequence: string |
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- name: diff_1 |
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dtype: 'null' |
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|
- name: diff_2 |
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|
dtype: 'null' |
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|
- name: diff_3 |
|
|
dtype: 'null' |
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|
- name: diff_4 |
|
|
dtype: 'null' |
|
|
- name: diff_5 |
|
|
dtype: 'null' |
|
|
- name: answer |
|
|
dtype: string |
|
|
- name: accepted_answers |
|
|
sequence: string |
|
|
- name: category |
|
|
dtype: string |
|
|
- name: task_type |
|
|
dtype: string |
|
|
- name: question_type |
|
|
sequence: string |
|
|
- name: metadata |
|
|
dtype: string |
|
|
splits: |
|
|
- name: agriexam |
|
|
num_bytes: 1816672 |
|
|
num_examples: 4548 |
|
|
- name: cca_ceu |
|
|
num_bytes: 345105 |
|
|
num_examples: 689 |
|
|
- name: embrapa |
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|
num_bytes: 32339083 |
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num_examples: 19682 |
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|
download_size: 14476971 |
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dataset_size: 34500860 |
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|
- config_name: agronomic_visual_cognition |
|
|
features: |
|
|
- name: id |
|
|
dtype: string |
|
|
- name: question |
|
|
dtype: string |
|
|
- name: images |
|
|
sequence: image |
|
|
- name: options |
|
|
struct: |
|
|
- name: default |
|
|
sequence: string |
|
|
- name: diff_1 |
|
|
sequence: string |
|
|
- name: diff_2 |
|
|
sequence: string |
|
|
- name: diff_3 |
|
|
sequence: string |
|
|
- name: diff_4 |
|
|
sequence: string |
|
|
- name: diff_5 |
|
|
sequence: string |
|
|
- name: answer |
|
|
dtype: string |
|
|
- name: accepted_answers |
|
|
sequence: string |
|
|
- name: category |
|
|
dtype: string |
|
|
- name: task_type |
|
|
dtype: string |
|
|
- name: question_type |
|
|
sequence: string |
|
|
- name: metadata |
|
|
dtype: string |
|
|
splits: |
|
|
- name: eppo |
|
|
num_bytes: 938281149.36 |
|
|
num_examples: 26428 |
|
|
- name: plantnet |
|
|
num_bytes: 2848270999.5 |
|
|
num_examples: 20350 |
|
|
- name: bppq |
|
|
num_bytes: 14213980 |
|
|
num_examples: 368 |
|
|
download_size: 3720715335 |
|
|
dataset_size: 3800766128.86 |
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configs: |
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- config_name: agricultural_procedural_reasoning |
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data_files: |
|
|
- split: wikihow_arrange |
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path: agricultural_procedural_reasoning/wikihow_arrange-* |
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|
- split: wikihow_missing |
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|
path: agricultural_procedural_reasoning/wikihow_missing-* |
|
|
- split: wikihow_next |
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|
path: agricultural_procedural_reasoning/wikihow_next-* |
|
|
- split: wikihow_all |
|
|
path: agricultural_procedural_reasoning/wikihow_all-* |
|
|
- config_name: agricultural_scientific_knowledge |
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|
data_files: |
|
|
- split: agriexam |
|
|
path: agricultural_scientific_knowledge/agriexam-* |
|
|
- split: cca_ceu |
|
|
path: agricultural_scientific_knowledge/cca_ceu-* |
|
|
- split: embrapa |
|
|
path: agricultural_scientific_knowledge/embrapa-* |
|
|
- config_name: agronomic_visual_cognition |
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default: true |
|
|
data_files: |
|
|
- split: eppo |
|
|
path: agronomic_visual_cognition/eppo-* |
|
|
- split: plantnet |
|
|
path: agronomic_visual_cognition/plantnet-* |
|
|
- split: bppq |
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|
path: agronomic_visual_cognition/bppq-* |
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|
license: cc-by-nc-nd-4.0 |
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task_categories: |
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|
- visual-question-answering |
|
|
- question-answering |
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|
- zero-shot-image-classification |
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- multiple-choice |
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language: |
|
|
- en |
|
|
pretty_name: CABBAGE |
|
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tags: |
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- biology |
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|
- agriculture |
|
|
--- |
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# 🥬 CABBAGE: Comprehensive Agricultural Benchmark Backed by AI-Guided Evaluation |
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[**🌐 Homepage**](https://huggingface.co/datasets/boilnserve/cabbage) | [**🏆 Leaderboard**](https://huggingface.co/datasets/boilnserve/cabbage) | [**🤗 Dataset**](https://huggingface.co/datasets/boilnserve/cabbage) | [**💻 GitHub**](https://github.com/boilnserve/cabbage) |
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## Table of Contents |
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|
- [CABBAGE: Comprehensive Agricultural Benchmark Backed by AI-Guided Evaluation](#%F0%9F%A5%AC-cabbage-comprehensive-agricultural-benchmark-backed-by-ai-guided-evaluation) |
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|
- [Table of Contents](#table-of-contents) |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#benchmark-tracks-and-subsets) |
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- [🖼️ Agronomic Visual Cognition](#%F0%9F%96%BC%EF%B8%8F-agronomic-visual-cognition) |
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- [📚 Agricultural Scientific Knowledge](#%F0%9F%93%9A-agricultural-scientific-knowledge) |
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- [🛠️ Agricultural Procedural Reasoning](#%F0%9F%9B%A0%EF%B8%8F-agricultural-procedural-reasoning) |
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- [Loading the Dataset](#loading-the-dataset) |
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## Dataset Description |
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- **Homepage:** https://huggingface.co/datasets/boilnserve/cabbage |
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- **Repository:** https://github.com/boilnserve/cabbage |
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- **Paper:** Not yet published |
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- **Leaderboard:** https://huggingface.co/datasets/boilnserve/cabbage |
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- **Size of downloaded dataset files:** 3.74 GB |
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- **Size of the auto-converted Parquet files:** 240.84 MB |
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- **Number of rows:** 74,206 |
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**CABBAGE** is a large-scale, multimodal benchmark for evaluating AI systems in agriculture across three complementary task macro-categories: **Visual Cognition**, **Scientific Knowledge**, and **Procedural Reasoning**. Each macro-category contains high-quality, domain-specific subsets built from curated or expert-reviewed sources. |
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## Benchmark Tracks and Subsets |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6824cf491019386a26b831c1/PYEaWom37vSKPDfKqt7fo.png" width="600"/> |
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### 🖼️ Agronomic Visual Cognition |
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Evaluates image-based plant understanding and visual QA. |
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- **`eppo`**: Plant pest and disease image classification (from EPPO data) |
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- **`plantnet`**: Species-level classification using Pl@ntNet imagery |
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- **`bppq`**: The Big Plant Pathology Quiz — visual QA for pathology |
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### 📚 Agricultural Scientific Knowledge |
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Tests scientific factual knowledge, retrieval, and reasoning over structured agronomic data. |
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- **`agriexam`**: Multiple-choice exams from official agricultural education materials |
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- **`cca_ceu`**: Multiple-choice questions from the Certified Crop Adviser datasets and Continuing Education Unit materials |
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- **`embrapa`**: Questions derived from Brazilian Agricultural Research Corporation technical guide series |
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### 🛠️ Agricultural Procedural Reasoning |
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Challenges models on procedural tasks derived from domain-relevant manuals and wikiHow entries. |
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- **`wikihow_arrange`**: Arrange steps of an agricultural procedure in the correct order |
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- **`wikihow_missing`**: Identify missing steps in an agricultural workflow |
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- **`wikihow_next`**: Predict the next step in a given task |
|
|
- **`wikihow_all`**: Generate the full sequence of steps required to carry out an agricultural task |
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## Loading the Dataset |
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You can load any specific configuration and split using the Hugging Face `datasets` library: |
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```python |
|
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from datasets import load_dataset |
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# Example: Load all the splits from the Agronomic Visual Cognition subset |
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dataset_dict = load_dataset("deepplants/cabbage", name="agronomic_visual_cognition") |
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# Example: Load the Embrapa split from the Agricultural Scientific Knowledge subset |
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dataset = load_dataset("deepplants/cabbage", name="agricultural_scientific_knowledge", split="embrapa") |
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``` |
