aiknowyou/all-mpnet-base-questions-clustering-en
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初始化项目，由ModelHub XC社区提供模型

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Model: aiknowyou/all-mpnet-base-questions-clustering-en
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2026-07-30 06:29:19 +08:00
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eval/binary_classification_evaluation_results.csv Normal file
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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
0,-1,0.9906596164909619,0.3930458724498749,0.9859670564400695,0.9870212179663819,0.9849151442492768,0.3930458724498749,0.9984901891426392,0.991234916691401,23.361751556396484,0.9868355558244485,0.9869576936405692,0.9867134482341425,23.616687774658203,0.9986105475645636,0.9906596164909619,1.1017749309539795,0.9859670564400695,0.9870212179663819,0.9849151442492768,1.1017749309539795,0.9984873210075305,0.9906596164909619,0.39304593205451965,0.9859670564400695,0.9870212179663819,0.9849151442492768,0.39304593205451965,0.9984897548380124
1,-1,0.9931843415744172,0.35143423080444336,0.9897547191636324,0.9913437348280885,0.9881707893839572,0.35143423080444336,0.9989950013637923,0.9934042015236294,24.160316467285156,0.9900818249442103,0.9920113508380628,0.9881597905828264,24.160316467285156,0.9990576126715013,0.9931843415744172,1.1389167308807373,0.9897547191636324,0.9913437348280885,0.9881707893839572,1.1389167308807373,0.9989921332302106,0.9931843415744172,0.35143429040908813,0.9897547191636324,0.9913437348280885,0.9881707893839572,0.35143429040908813,0.9989933009226604
1 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
2 0 -1 0.9906596164909619 0.3930458724498749 0.9859670564400695 0.9870212179663819 0.9849151442492768 0.3930458724498749 0.9984901891426392 0.991234916691401 23.361751556396484 0.9868355558244485 0.9869576936405692 0.9867134482341425 23.616687774658203 0.9986105475645636 0.9906596164909619 1.1017749309539795 0.9859670564400695 0.9870212179663819 0.9849151442492768 1.1017749309539795 0.9984873210075305 0.9906596164909619 0.39304593205451965 0.9859670564400695 0.9870212179663819 0.9849151442492768 0.39304593205451965 0.9984897548380124
3 1 -1 0.9931843415744172 0.35143423080444336 0.9897547191636324 0.9913437348280885 0.9881707893839572 0.35143423080444336 0.9989950013637923 0.9934042015236294 24.160316467285156 0.9900818249442103 0.9920113508380628 0.9881597905828264 24.160316467285156 0.9990576126715013 0.9931843415744172 1.1389167308807373 0.9897547191636324 0.9913437348280885 0.9881707893839572 1.1389167308807373 0.9989921332302106 0.9931843415744172 0.35143429040908813 0.9897547191636324 0.9913437348280885 0.9881707893839572 0.35143429040908813 0.9989933009226604