cross-encoder/quora-distilroberta-base
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初始化项目，由ModelHub XC社区提供模型

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Model: cross-encoder/quora-distilroberta-base
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2026-05-13 16:50:07 +08:00
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CEBinaryClassificationEvaluator_Quora-dev_results.csv Normal file
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epoch,steps,Accuracy,Accuracy_Threshold,F1,F1_Threshold,Precision,Recall,Average_Precision
0,5000,0.8452570933975277,0.2983477711677551,0.7900497512437811,0.18507549166679382,0.7322310783215862,0.8577822362836639,0.8396229747981989
0,10000,0.857347650861486,0.5213649272918701,0.8031484845246999,0.33029448986053467,0.7457997089562112,0.8700517015201791,0.8545970007991148
0,15000,0.8609721132779746,0.1738070547580719,0.8078387142252925,0.04706580936908722,0.7435281904885487,0.8843274944054326,0.8683121532515892
0,20000,0.8651104920072489,0.47281914949417114,0.8140117360812937,0.28083980083465576,0.7588898525585429,0.8777683463230187,0.8688431110199832
0,25000,0.8627572962592303,0.3951731324195862,0.8135375846099039,0.1231781542301178,0.7556084971213024,0.8810865035882398,0.8680829287785565
0,30000,0.8675989288902113,0.23542040586471558,0.8190337283500455,0.15778020024299622,0.7763721830499102,0.8666563778069295,0.8753982019828903
0,-1,0.8682751345649292,0.18975578248500824,0.8190918322936311,0.1217166930437088,0.7727366043933483,0.8713635311366618,0.8752323608217697
1,5000,0.8672202537123691,0.11032938957214355,0.8186121022354911,0.06648033857345581,0.7749362376783622,0.867505208735242,0.8734906535795933
1,10000,0.868789050877715,0.39354807138442993,0.820622596328278,0.14097964763641357,0.7744299116619873,0.8726753607531446,0.8753506581928413
1,15000,0.8691406778285683,0.14086419343948364,0.8205202207871857,0.04024771973490715,0.7704607046070461,0.8775368469789335,0.8762103576779169
1,20000,0.8707094749939142,0.12691470980644226,0.8241213305824012,0.04960266500711441,0.7761112626124897,0.8784628443552743,0.8740756841801574
1,25000,0.8700062210922074,0.09521728754043579,0.8238741182854042,0.05193943902850151,0.7754323845839575,0.878771510147388,0.8754125303894846
1,30000,0.8710611019447675,0.13264580070972443,0.8236196879453356,0.06295235455036163,0.7822043309272626,0.8696658692800371,0.8759877493381109
1,-1,0.8706824267669254,0.06451858580112457,0.8241568175266647,0.03969372808933258,0.7730683431352667,0.882475499652751,0.8747959164698776
1 epoch steps Accuracy Accuracy_Threshold F1 F1_Threshold Precision Recall Average_Precision
2 0 5000 0.8452570933975277 0.2983477711677551 0.7900497512437811 0.18507549166679382 0.7322310783215862 0.8577822362836639 0.8396229747981989
3 0 10000 0.857347650861486 0.5213649272918701 0.8031484845246999 0.33029448986053467 0.7457997089562112 0.8700517015201791 0.8545970007991148
4 0 15000 0.8609721132779746 0.1738070547580719 0.8078387142252925 0.04706580936908722 0.7435281904885487 0.8843274944054326 0.8683121532515892
5 0 20000 0.8651104920072489 0.47281914949417114 0.8140117360812937 0.28083980083465576 0.7588898525585429 0.8777683463230187 0.8688431110199832
6 0 25000 0.8627572962592303 0.3951731324195862 0.8135375846099039 0.1231781542301178 0.7556084971213024 0.8810865035882398 0.8680829287785565
7 0 30000 0.8675989288902113 0.23542040586471558 0.8190337283500455 0.15778020024299622 0.7763721830499102 0.8666563778069295 0.8753982019828903
8 0 -1 0.8682751345649292 0.18975578248500824 0.8190918322936311 0.1217166930437088 0.7727366043933483 0.8713635311366618 0.8752323608217697
9 1 5000 0.8672202537123691 0.11032938957214355 0.8186121022354911 0.06648033857345581 0.7749362376783622 0.867505208735242 0.8734906535795933
10 1 10000 0.868789050877715 0.39354807138442993 0.820622596328278 0.14097964763641357 0.7744299116619873 0.8726753607531446 0.8753506581928413
11 1 15000 0.8691406778285683 0.14086419343948364 0.8205202207871857 0.04024771973490715 0.7704607046070461 0.8775368469789335 0.8762103576779169
12 1 20000 0.8707094749939142 0.12691470980644226 0.8241213305824012 0.04960266500711441 0.7761112626124897 0.8784628443552743 0.8740756841801574
13 1 25000 0.8700062210922074 0.09521728754043579 0.8238741182854042 0.05193943902850151 0.7754323845839575 0.878771510147388 0.8754125303894846
14 1 30000 0.8710611019447675 0.13264580070972443 0.8236196879453356 0.06295235455036163 0.7822043309272626 0.8696658692800371 0.8759877493381109
15 1 -1 0.8706824267669254 0.06451858580112457 0.8241568175266647 0.03969372808933258 0.7730683431352667 0.882475499652751 0.8747959164698776