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Browse files- README.md +4 -1
- eval/binary_classification_evaluation_results.csv +9 -9
- pytorch_model.bin +1 -1
README.md
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@@ -92,7 +92,10 @@ The model was trained with the parameters:
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**Loss**:
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`sentence_transformers.losses.
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Parameters of the fit()-Method:
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```
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**Loss**:
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`sentence_transformers.losses.ContrastiveLoss.ContrastiveLoss` with parameters:
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```
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{'distance_metric': 'SiameseDistanceMetric.COSINE_DISTANCE', 'margin': 0.5, 'size_average': True}
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```
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Parameters of the fit()-Method:
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```
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eval/binary_classification_evaluation_results.csv
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epoch,steps,cossim_accuracy,cossim_accuracy_threshold,cossim_f1,cossim_precision,cossim_recall,cossim_f1_threshold,cossim_ap,manhattan_accuracy,manhattan_accuracy_threshold,manhattan_f1,manhattan_precision,manhattan_recall,manhattan_f1_threshold,manhattan_ap,euclidean_accuracy,euclidean_accuracy_threshold,euclidean_f1,euclidean_precision,euclidean_recall,euclidean_f1_threshold,euclidean_ap,dot_accuracy,dot_accuracy_threshold,dot_f1,dot_precision,dot_recall,dot_f1_threshold,dot_ap
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0,250,0.
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0,500,0.
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0,-1,0.
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1,250,0.
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1,500,0.
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1,-1,0.
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2,250,0.
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2,500,0.
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2,-1,0.
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epoch,steps,cossim_accuracy,cossim_accuracy_threshold,cossim_f1,cossim_precision,cossim_recall,cossim_f1_threshold,cossim_ap,manhattan_accuracy,manhattan_accuracy_threshold,manhattan_f1,manhattan_precision,manhattan_recall,manhattan_f1_threshold,manhattan_ap,euclidean_accuracy,euclidean_accuracy_threshold,euclidean_f1,euclidean_precision,euclidean_recall,euclidean_f1_threshold,euclidean_ap,dot_accuracy,dot_accuracy_threshold,dot_f1,dot_precision,dot_recall,dot_f1_threshold,dot_ap
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pytorch_model.bin
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