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--- |
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license: cc-by-nc-4.0 |
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task_categories: |
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- tabular-classification |
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language: |
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- en |
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tags: |
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- evaluation |
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- metrics |
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- setfit |
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- water-conflict |
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- multi-label-classification |
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size_categories: |
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- n<1K |
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pretty_name: Water Conflict Classifier Evaluation Metrics |
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--- |
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# Water Conflict Classifier Evaluation Metrics |
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Evaluation metrics tracking the performance of the [Water Conflict Classifier](https://huggingface.co/baobabtech/water-conflict-classifier) across multiple training iterations and model configurations. |
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## Dataset Summary |
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This dataset contains evaluation results from training runs of the Water Conflict Classifier, a multi-label SetFit model that identifies water-related conflict events in news headlines. Each row represents one model version with comprehensive performance metrics across three classification labels: Trigger, Casualty, and Weapon. |
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**Related Links:** |
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- 🤗 [Model Collection](https://huggingface.co/collections/baobabtech/water-conflict-classifier) |
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- 🐙 [GitHub Repository](https://github.com/baobab-tech/waterconflict) |
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- 📦 [PyPI Package](https://pypi.org/project/water-conflict-classifier/) |
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- 🌊 [Pacific Institute Water Conflict Chronology](https://www.worldwater.org/water-conflict/) |
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## Dataset Structure |
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### Fields |
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| Field | Type | Description | |
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|-------|------|-------------| |
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| `version` | string | Model version identifier (v1.0, v2.0, etc.) | |
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| `timestamp` | string | Training completion timestamp | |
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| `base_model` | string | Base embedding model used | |
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| `train_size` | int | Number of training examples | |
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| `test_size` | int | Number of test examples | |
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| `f1_micro` | float | Micro-averaged F1 score | |
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| `f1_macro` | float | Macro-averaged F1 score | |
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| `accuracy` | float | Overall accuracy | |
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| `trigger_*` | float | Precision/recall/F1 for Trigger label | |
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| `casualty_*` | float | Precision/recall/F1 for Casualty label | |
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| `weapon_*` | float | Precision/recall/F1 for Weapon label | |
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| `model_repo` | string | HuggingFace model repository | |
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### Model Versions |
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The dataset tracks performance across different configurations: |
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- Base models: BAAI/bge-small-en-v1.5, sentence-transformers/all-MiniLM-L6-v2 |
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- Training strategies: undersampling for class balance |
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- Hyperparameter variations: batch size, epochs, sample size |
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## Usage |
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```python |
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from datasets import load_dataset |
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# Load the evaluation metrics |
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evals = load_dataset("baobabtech/water-conflict-classifier-evals") |
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# Compare model versions |
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import pandas as pd |
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df = pd.DataFrame(evals['train']) |
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print(df[['version', 'f1_macro', 'accuracy']].sort_values('f1_macro', ascending=False)) |
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``` |
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## Citation |
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If you use this dataset or the Water Conflict Classifier in your research, please cite: |
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```bibtex |
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@misc{baobab_water_conflict_classifier, |
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author = {Mills, Olivier}, |
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title = {Water Conflict Classifier: Few-Shot Learning for Water-Related Conflict Event Detection}, |
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year = {2025}, |
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publisher = {Hugging Face}, |
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howpublished = {\url{https://huggingface.co/baobabtech/water-conflict-classifier}} |
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} |
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``` |
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## License |
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CC-BY-NC-4.0 (Non-commercial use only) |
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## Contact |
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**Olivier Mills** |
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Website: [baobabtech.ai](https://baobabtech.ai) |
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LinkedIn: [oliviermills](https://www.linkedin.com/in/oliviermills/) |
