Update model card with evaluation results from goldset from ner_disorderfinding_de_goldset

README.md

@@ -68,3 +68,38 @@ The following hyperparameters were used during training:
 - Pytorch 2.6.0+cu124
 - Datasets 2.16.0
 - Tokenizers 0.20.3
+
+
+## Model Performance
+
+This model has been evaluated on the **goldset from ner_disorderfinding_de_goldset** using
+IO evaluation (sklearn, token level, lenient) with the following results:
+
+### Overall Performance
+
+| Metric | Score |
+|--------|-------|
+| Precision (Macro) | 0.425082 |
+| Recall (Macro) | 0.467785 |
+| F1-Score (Macro) | 0.435900 |
+| Precision (Weighted) | 0.600185 |
+| Recall (Weighted) | 0.698514 |
+| F1-Score (Weighted) | 0.640943 |
+
+**Inference Performance**: 5.51 seconds for evaluation dataset
+
+### Entity-Level Performance (IO Evaluation)
+
+| Entity Type | Precision | Recall | F1-Score | Support |
+|-------------|-----------|--------|----------|---------|
+| DISORDER_FINDING | 0.753771 | 0.900890 | 0.820790 | N/A |
+
+### Evaluation Details
+
+- **Dataset**: goldset from ner_disorderfinding_de_goldset
+- **Dataset Source**: goldset
+- **Evaluation Date**: 2025-09-25 09:43:46
+- **Language**: de
+- **Entities**: DISORDER_FINDING
+
+*This evaluation section is automatically generated and updated.*