Update README.md

Biodiversity Commitment Specificity Classifier

Model Overview
This binary text classification model evaluates the specificity of biodiversity commitments in corporate sustainability reports. Designed as a second-stage classifier for paragraphs already identified as commitments, it distinguishes between:

Specific: Commitments detailing concrete actions, measurable targets, clear strategies, or verifiable implementation plans
Non-specific: Vague, ambiguous, or unverifiable commitment statements

Model Architecture
Built on ClimateBERT, a DistilRoBERTa-based model pre-trained on climate-related text, this classifier was fine-tuned to assess commitment specificity in corporate biodiversity disclosures.

Training Data
The model was trained on a curated dataset of 2,000 manually annotated paragraphs extracted from sustainability reports of Fortune Global 500 companies

Performance Metrics
Evaluated using 5-fold cross-validation:
MetricScoreWeighted F10.856Weighted Precision0.857Weighted Recall0.856AUC-ROC0.922

Pipeline Recommendation
For optimal results, use this model in combination with our commitment detection model:

Stage 1: Identify biodiversity-related commitments
Stage 2: Classify commitment specificity (this model)

README.md

@@ -1,3 +1,26 @@
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-license: apache-2.0
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+---
+license: apache-2.0
+---
+Biodiversity Commitment Specificity Classifier
+
+Model Overview
+This binary text classification model evaluates the specificity of biodiversity commitments in corporate sustainability reports. Designed as a second-stage classifier for paragraphs already identified as commitments, it distinguishes between:
+
+Specific: Commitments detailing concrete actions, measurable targets, clear strategies, or verifiable implementation plans
+Non-specific: Vague, ambiguous, or unverifiable commitment statements 
+
+Model Architecture
+Built on ClimateBERT, a DistilRoBERTa-based model pre-trained on climate-related text, this classifier was fine-tuned to assess commitment specificity in corporate biodiversity disclosures.
+
+Training Data
+The model was trained on a curated dataset of 2,000 manually annotated paragraphs extracted from sustainability reports of Fortune Global 500 companies
+
+Performance Metrics
+Evaluated using 5-fold cross-validation:
+MetricScoreWeighted F10.856Weighted Precision0.857Weighted Recall0.856AUC-ROC0.922
+
+Pipeline Recommendation
+For optimal results, use this model in combination with our commitment detection model:
+
+Stage 1: Identify biodiversity-related commitments
+Stage 2: Classify commitment specificity (this model)