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Add script: evaluate
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Run python scripts/evaluate.py <classifier> to run the benchmark on the
given classifier. This automatically (re-)writes results.csv, stats.csv
and README.md for the given classifier.
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FinnWoelm committed Mar 16, 2024
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16 changes: 7 additions & 9 deletions README.md
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Expand Up @@ -16,7 +16,7 @@ The SDG Classification Benchmarking Dataset is an open and public resource for e
- [Non-exhaustive](#non-exhaustive)
- [Non-sentimental](#non-sentimental)
- [Non-interpretive](#non-interpretive)
- [Model results (pending)](#model-results-pending)
- [Model results](#model-results)
- [Contributing](#contributing)
- [Join the working group](#join-the-working-group)
- [Suggestions and feedback](#suggestions-and-feedback)
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We ignored indirect relevance in texts because correct assessments would require enormous thematic expertise, and even then such interpretations would often remain highly subjective and controversial.

## Model results (pending)

This section is pending.
## Model results

The table below shows the accuracy (in percent) of SDG classification models when evaluated against this benchmarking dataset:

| Model | SDG 7 |
| -------- | ----: |
| example1 | 83 |
| example2 | 79 |
| example3 | 82 |
| Model | SDG 7 |
| ----------------------------------------- | ----: |
| [JRC SDG Mapper](evaluations/sdg-mapper/) | 86 |

More models will be added in the future.

Have you benchmarked a model that is not yet in our list? Please open an issue and share the results with us, so that we can add the model to the table above.

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13 changes: 13 additions & 0 deletions evaluations/README.template.md
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# {{name}}

{{about}}

Learn more: {{url}}

## Evaluation

{{stats}}

**Benchmarked on**: {{date}}

**Detailed benchmark results**: [results.csv](results.csv)
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