gwlms
/

span-marker-bert-germeval14

Token Classification

named-entity-recognition

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stefan-it commited on Aug 18, 2023

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7422d6b

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readme: fix table

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@@ -59,9 +59,9 @@ Evaluation is performed with SpanMarkers internal evaluation code that uses `seq
 We fine-tune 5 models and upload the model with best F1-Score on development set. Results on development set are
 in brackets:
-| Model                  | Run 1           | Run 2           | Run 3           | Run 4           | Run 5               | Avg.
-| ---------------------- | --------------- | --------------- | --------------- | --------------- | ------------------- | ---------------
-| GWLMS BERT (5e-05, 3e) | (87.27) / 87.28 | (87.20) / 87.42 | (88.05) / 87.68 | (88.25) / 87.59 | (**88.47**) / 87.45 | (87.85) / 87.48
 The best model achieves a final test score of 87.45%.

 We fine-tune 5 models and upload the model with best F1-Score on development set. Results on development set are
 in brackets:
+| Model      | Run 1           | Run 2           | Run 3           | Run 4           | Run 5               | Avg.
+| ---------- | --------------- | --------------- | --------------- | --------------- | ------------------- | ---------------
+| GWLMS BERT | (87.27) / 87.28 | (87.20) / 87.42 | (88.05) / 87.68 | (88.25) / 87.59 | (**88.47**) / 87.45 | (87.85) / 87.48
 The best model achieves a final test score of 87.45%.