radoslavralev commited on
Commit
ef4e0fd
·
verified ·
1 Parent(s): 15aa90c

Training in progress, step 3000

Browse files
Information-Retrieval_evaluation_BeIR-touche2020-subset-test_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.7551020408163265,0.8979591836734694,0.9387755102040817,1.0,0.7551020408163265,0.01681883497544576,0.6802721088435373,0.045273391320759554,0.6489795918367346,0.07198855467813525,0.563265306122449,0.12417651370073833,0.8328474246841594,0.6023501966395867,0.2434385293084787
3
  -1,-1,0.7142857142857143,0.8979591836734694,0.9387755102040817,0.9795918367346939,0.7142857142857143,0.015888088527206596,0.6802721088435375,0.04529851299481363,0.6204081632653061,0.06854028378310305,0.5469387755102041,0.12037980510830988,0.8197278911564625,0.5854787058529846,0.2463904322921895
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.7551020408163265,0.8979591836734694,0.9387755102040817,1.0,0.7551020408163265,0.01681883497544576,0.6802721088435373,0.045273391320759554,0.6489795918367346,0.07198855467813525,0.563265306122449,0.12417651370073833,0.8328474246841594,0.6023501966395867,0.2434385293084787
3
  -1,-1,0.7142857142857143,0.8979591836734694,0.9387755102040817,0.9795918367346939,0.7142857142857143,0.015888088527206596,0.6802721088435375,0.04529851299481363,0.6204081632653061,0.06854028378310305,0.5469387755102041,0.12037980510830988,0.8197278911564625,0.5854787058529846,0.2463904322921895
4
+ -1,-1,0.6938775510204082,0.9183673469387755,0.9387755102040817,1.0,0.6938775510204082,0.015282578640721299,0.6598639455782312,0.043691811612696696,0.6204081632653061,0.06836863756086255,0.5448979591836733,0.12002846003612215,0.802437641723356,0.5792925091922296,0.23820124526811953
Information-Retrieval_evaluation_NanoArguAna_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.18,0.5,0.66,0.74,0.18,0.18,0.16666666666666663,0.5,0.13200000000000003,0.66,0.07400000000000001,0.74,0.3599682539682539,0.45218312003145433,0.3658170202780539
3
  -1,-1,0.04,0.18,0.2,0.34,0.04,0.04,0.06,0.18,0.04,0.2,0.034,0.34,0.12532539682539678,0.175419302465962,0.14459756648011524
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.18,0.5,0.66,0.74,0.18,0.18,0.16666666666666663,0.5,0.13200000000000003,0.66,0.07400000000000001,0.74,0.3599682539682539,0.45218312003145433,0.3658170202780539
3
  -1,-1,0.04,0.18,0.2,0.34,0.04,0.04,0.06,0.18,0.04,0.2,0.034,0.34,0.12532539682539678,0.175419302465962,0.14459756648011524
4
+ -1,-1,0.08,0.18,0.24,0.34,0.08,0.08,0.06,0.18,0.04800000000000001,0.24,0.034,0.34,0.1541031746031746,0.19775950107880547,0.1637127723917234
Information-Retrieval_evaluation_NanoClimateFEVER_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.1,0.32,0.44,0.6,0.1,0.04333333333333333,0.11333333333333333,0.154,0.092,0.214,0.066,0.2723333333333333,0.23579365079365078,0.18832347198247595,0.13278630044723194
3
  -1,-1,0.14,0.22,0.26,0.38,0.14,0.07,0.07333333333333333,0.11066666666666666,0.05200000000000001,0.13566666666666666,0.038,0.19066666666666665,0.20153968253968252,0.1453885297185151,0.10907272614067173
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.1,0.32,0.44,0.6,0.1,0.04333333333333333,0.11333333333333333,0.154,0.092,0.214,0.066,0.2723333333333333,0.23579365079365078,0.18832347198247595,0.13278630044723194
3
  -1,-1,0.14,0.22,0.26,0.38,0.14,0.07,0.07333333333333333,0.11066666666666666,0.05200000000000001,0.13566666666666666,0.038,0.19066666666666665,0.20153968253968252,0.1453885297185151,0.10907272614067173
4
+ -1,-1,0.1,0.16,0.18,0.36,0.1,0.039,0.05333333333333333,0.07233333333333332,0.04,0.09899999999999999,0.038000000000000006,0.17800000000000002,0.15424603174603174,0.1173759125527998,0.08470650399139114
Information-Retrieval_evaluation_NanoDBPedia_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.58,0.82,0.86,0.88,0.58,0.05774032197349101,0.5266666666666666,0.13525154291594316,0.444,0.17429307751101658,0.36199999999999993,0.24557535689700863,0.7,0.46037876007701023,0.32047705412103555
3
  -1,-1,0.52,0.72,0.82,0.86,0.52,0.047202979496018524,0.4,0.10194727189869665,0.364,0.15730653946206946,0.30000000000000004,0.22246963483004237,0.6298333333333334,0.38619002202024644,0.2319232549425231
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.58,0.82,0.86,0.88,0.58,0.05774032197349101,0.5266666666666666,0.13525154291594316,0.444,0.17429307751101658,0.36199999999999993,0.24557535689700863,0.7,0.46037876007701023,0.32047705412103555
3
  -1,-1,0.52,0.72,0.82,0.86,0.52,0.047202979496018524,0.4,0.10194727189869665,0.364,0.15730653946206946,0.30000000000000004,0.22246963483004237,0.6298333333333334,0.38619002202024644,0.2319232549425231
4
+ -1,-1,0.54,0.76,0.84,0.9,0.54,0.07619799906535789,0.42,0.1276779058713768,0.384,0.16749620234443643,0.29200000000000004,0.21087586592616692,0.6681666666666666,0.3969317585871071,0.25479322904197393
Information-Retrieval_evaluation_NanoFEVER_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.56,0.8,0.88,0.88,0.56,0.5266666666666666,0.28,0.7533333333333333,0.184,0.8333333333333333,0.092,0.8333333333333333,0.6789999999999999,0.7016221865098926,0.6483203115492273
3
  -1,-1,0.28,0.52,0.6,0.68,0.28,0.27,0.1733333333333333,0.49,0.12,0.57,0.07,0.65,0.4225238095238095,0.4689004130810094,0.4118080771584329
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.56,0.8,0.88,0.88,0.56,0.5266666666666666,0.28,0.7533333333333333,0.184,0.8333333333333333,0.092,0.8333333333333333,0.6789999999999999,0.7016221865098926,0.6483203115492273
3
  -1,-1,0.28,0.52,0.6,0.68,0.28,0.27,0.1733333333333333,0.49,0.12,0.57,0.07,0.65,0.4225238095238095,0.4689004130810094,0.4118080771584329
4
+ -1,-1,0.3,0.44,0.52,0.58,0.3,0.28,0.14666666666666667,0.41,0.10800000000000001,0.5,0.062,0.56,0.39605555555555555,0.4268388511477842,0.3890457012149144
Information-Retrieval_evaluation_NanoFiQA2018_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.24,0.38,0.42,0.52,0.24,0.13307936507936508,0.15333333333333332,0.21543650793650795,0.11600000000000002,0.2601031746031746,0.07600000000000001,0.3241587301587302,0.3178809523809524,0.2635447070179544,0.22615568818713977
3
  -1,-1,0.26,0.36,0.4,0.48,0.26,0.1585238095238095,0.13999999999999999,0.2282698412698413,0.10000000000000002,0.2517936507936508,0.064,0.3186825396825397,0.3242460317460317,0.26876133900480464,0.24128551555161426
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.24,0.38,0.42,0.52,0.24,0.13307936507936508,0.15333333333333332,0.21543650793650795,0.11600000000000002,0.2601031746031746,0.07600000000000001,0.3241587301587302,0.3178809523809524,0.2635447070179544,0.22615568818713977
3
  -1,-1,0.26,0.36,0.4,0.48,0.26,0.1585238095238095,0.13999999999999999,0.2282698412698413,0.10000000000000002,0.2517936507936508,0.064,0.3186825396825397,0.3242460317460317,0.26876133900480464,0.24128551555161426
4
+ -1,-1,0.22,0.34,0.44,0.6,0.22,0.11407936507936509,0.15333333333333332,0.21912698412698411,0.124,0.2806825396825397,0.094,0.4115714285714286,0.3207142857142857,0.29458681641245554,0.23364616122992465
Information-Retrieval_evaluation_NanoHotpotQA_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.5,0.58,0.62,0.68,0.5,0.25,0.2333333333333333,0.35,0.16399999999999998,0.41,0.094,0.47,0.5529999999999999,0.43627646197603637,0.37828612061221206
3
  -1,-1,0.54,0.66,0.74,0.84,0.54,0.27,0.2533333333333333,0.38,0.17600000000000002,0.44,0.10599999999999998,0.53,0.6256031746031746,0.4749742091237649,0.38794691370738704
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.5,0.58,0.62,0.68,0.5,0.25,0.2333333333333333,0.35,0.16399999999999998,0.41,0.094,0.47,0.5529999999999999,0.43627646197603637,0.37828612061221206
3
  -1,-1,0.54,0.66,0.74,0.84,0.54,0.27,0.2533333333333333,0.38,0.17600000000000002,0.44,0.10599999999999998,0.53,0.6256031746031746,0.4749742091237649,0.38794691370738704
4
+ -1,-1,0.52,0.68,0.74,0.78,0.52,0.26,0.2733333333333334,0.41,0.184,0.46,0.102,0.51,0.6083333333333334,0.46561524553654626,0.3863310446433211
Information-Retrieval_evaluation_NanoMSMARCO_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.26,0.52,0.6,0.62,0.26,0.26,0.1733333333333333,0.52,0.12,0.6,0.062,0.62,0.40519047619047627,0.45904886208148177,0.4260102142025637
3
  -1,-1,0.28,0.38,0.42,0.56,0.28,0.28,0.12666666666666665,0.38,0.084,0.42,0.05600000000000001,0.56,0.3516904761904761,0.4001173610020243,0.37336992686291426
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.26,0.52,0.6,0.62,0.26,0.26,0.1733333333333333,0.52,0.12,0.6,0.062,0.62,0.40519047619047627,0.45904886208148177,0.4260102142025637
3
  -1,-1,0.28,0.38,0.42,0.56,0.28,0.28,0.12666666666666665,0.38,0.084,0.42,0.05600000000000001,0.56,0.3516904761904761,0.4001173610020243,0.37336992686291426
4
+ -1,-1,0.22,0.42,0.56,0.64,0.22,0.22,0.13999999999999999,0.42,0.11200000000000002,0.56,0.06400000000000002,0.64,0.3573571428571428,0.4253611031601517,0.37029891648053065
Information-Retrieval_evaluation_NanoNFCorpus_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.32,0.5,0.52,0.64,0.32,0.01260685895239504,0.31333333333333335,0.03463231741620742,0.27599999999999997,0.06850002262294216,0.24399999999999994,0.10851262864104039,0.4212380952380952,0.2703690747449406,0.10029196368651581
3
  -1,-1,0.36,0.46,0.5,0.56,0.36,0.01309333347305052,0.2733333333333333,0.029796345008688278,0.256,0.04461630481223397,0.21799999999999997,0.06880715289816099,0.4221111111111111,0.24206789327168107,0.08443685448289194
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.32,0.5,0.52,0.64,0.32,0.01260685895239504,0.31333333333333335,0.03463231741620742,0.27599999999999997,0.06850002262294216,0.24399999999999994,0.10851262864104039,0.4212380952380952,0.2703690747449406,0.10029196368651581
3
  -1,-1,0.36,0.46,0.5,0.56,0.36,0.01309333347305052,0.2733333333333333,0.029796345008688278,0.256,0.04461630481223397,0.21799999999999997,0.06880715289816099,0.4221111111111111,0.24206789327168107,0.08443685448289194
4
+ -1,-1,0.32,0.46,0.54,0.6,0.32,0.012390714058566699,0.28,0.03091743967375776,0.26,0.0669147297391448,0.222,0.09088305778625912,0.4105238095238095,0.2483348722648785,0.09280425392585814
Information-Retrieval_evaluation_NanoNQ_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.32,0.5,0.6,0.62,0.32,0.3,0.1733333333333333,0.47,0.128,0.58,0.066,0.6,0.4272222222222222,0.4619884812398348,0.42411983365963474
3
  -1,-1,0.24,0.32,0.38,0.44,0.24,0.23,0.10666666666666665,0.3,0.07600000000000001,0.35,0.046,0.42,0.30133333333333334,0.32272214750507383,0.3026672483997021
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.32,0.5,0.6,0.62,0.32,0.3,0.1733333333333333,0.47,0.128,0.58,0.066,0.6,0.4272222222222222,0.4619884812398348,0.42411983365963474
3
  -1,-1,0.24,0.32,0.38,0.44,0.24,0.23,0.10666666666666665,0.3,0.07600000000000001,0.35,0.046,0.42,0.30133333333333334,0.32272214750507383,0.3026672483997021
4
+ -1,-1,0.18,0.34,0.4,0.48,0.18,0.16,0.11333333333333333,0.32,0.08,0.37,0.04800000000000001,0.45,0.27455555555555555,0.30483462455030724,0.26647869540792385
Information-Retrieval_evaluation_NanoQuoraRetrieval_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.94,1.0,1.0,1.0,0.94,0.8273333333333334,0.4133333333333333,0.9653333333333333,0.25999999999999995,0.9793333333333334,0.13799999999999998,0.9966666666666666,0.9666666666666667,0.9697624312418531,0.9551233766233765
3
  -1,-1,0.94,0.98,1.0,1.0,0.94,0.8273333333333334,0.40666666666666657,0.9453333333333334,0.264,0.986,0.13799999999999998,0.9966666666666666,0.9616666666666667,0.9649140578691123,0.9493650793650792
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.94,1.0,1.0,1.0,0.94,0.8273333333333334,0.4133333333333333,0.9653333333333333,0.25999999999999995,0.9793333333333334,0.13799999999999998,0.9966666666666666,0.9666666666666667,0.9697624312418531,0.9551233766233765
3
  -1,-1,0.94,0.98,1.0,1.0,0.94,0.8273333333333334,0.40666666666666657,0.9453333333333334,0.264,0.986,0.13799999999999998,0.9966666666666666,0.9616666666666667,0.9649140578691123,0.9493650793650792
4
+ -1,-1,0.96,0.98,1.0,1.0,0.96,0.8373333333333332,0.4133333333333333,0.9520000000000001,0.25999999999999995,0.9793333333333334,0.13999999999999999,1.0,0.975,0.9755732089084438,0.9623253968253969
Information-Retrieval_evaluation_NanoSCIDOCS_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.42,0.6,0.72,0.82,0.42,0.08866666666666667,0.33333333333333326,0.20866666666666664,0.272,0.2806666666666667,0.17999999999999997,0.3696666666666666,0.540047619047619,0.36082794471047336,0.2862806075456748
3
  -1,-1,0.42,0.6,0.72,0.8,0.42,0.08700000000000001,0.2933333333333333,0.18100000000000002,0.24800000000000005,0.25666666666666665,0.16399999999999998,0.33666666666666656,0.5280555555555556,0.3309587311349605,0.2571164275500479
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.42,0.6,0.72,0.82,0.42,0.08866666666666667,0.33333333333333326,0.20866666666666664,0.272,0.2806666666666667,0.17999999999999997,0.3696666666666666,0.540047619047619,0.36082794471047336,0.2862806075456748
3
  -1,-1,0.42,0.6,0.72,0.8,0.42,0.08700000000000001,0.2933333333333333,0.18100000000000002,0.24800000000000005,0.25666666666666665,0.16399999999999998,0.33666666666666656,0.5280555555555556,0.3309587311349605,0.2571164275500479
4
+ -1,-1,0.44,0.66,0.76,0.82,0.44,0.09100000000000001,0.3533333333333333,0.22066666666666668,0.29200000000000004,0.3016666666666667,0.18799999999999997,0.38666666666666655,0.5660238095238094,0.3759831673953289,0.2923958742502536
Information-Retrieval_evaluation_NanoSciFact_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.38,0.46,0.5,0.58,0.38,0.345,0.15999999999999998,0.43,0.10800000000000003,0.475,0.068,0.58,0.44026984126984126,0.46384622999765257,0.43257979600699104
3
  -1,-1,0.2,0.28,0.34,0.4,0.2,0.175,0.1,0.24,0.07200000000000001,0.3,0.046000000000000006,0.37,0.2611904761904762,0.2742062576081037,0.25107673217045623
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.38,0.46,0.5,0.58,0.38,0.345,0.15999999999999998,0.43,0.10800000000000003,0.475,0.068,0.58,0.44026984126984126,0.46384622999765257,0.43257979600699104
3
  -1,-1,0.2,0.28,0.34,0.4,0.2,0.175,0.1,0.24,0.07200000000000001,0.3,0.046000000000000006,0.37,0.2611904761904762,0.2742062576081037,0.25107673217045623
4
+ -1,-1,0.22,0.3,0.32,0.38,0.22,0.195,0.12,0.285,0.07600000000000001,0.305,0.044000000000000004,0.365,0.2718333333333333,0.28918208458247957,0.27817432559902106
Information-Retrieval_evaluation_NanoTouche2020_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.46938775510204084,0.8367346938775511,0.9387755102040817,1.0,0.46938775510204084,0.032657982947973084,0.44897959183673464,0.09621881460341672,0.42040816326530606,0.1425551052100505,0.3346938775510204,0.22061476067159091,0.6573129251700679,0.3807140713282222,0.2698119698398041
3
  -1,-1,0.40816326530612246,0.7142857142857143,0.8367346938775511,0.9387755102040817,0.40816326530612246,0.026947689355902065,0.3945578231292517,0.08175620968668966,0.3591836734693878,0.11912284095947995,0.3142857142857143,0.20232769620294389,0.584402332361516,0.3489871366097425,0.24268590817987387
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.46938775510204084,0.8367346938775511,0.9387755102040817,1.0,0.46938775510204084,0.032657982947973084,0.44897959183673464,0.09621881460341672,0.42040816326530606,0.1425551052100505,0.3346938775510204,0.22061476067159091,0.6573129251700679,0.3807140713282222,0.2698119698398041
3
  -1,-1,0.40816326530612246,0.7142857142857143,0.8367346938775511,0.9387755102040817,0.40816326530612246,0.026947689355902065,0.3945578231292517,0.08175620968668966,0.3591836734693878,0.11912284095947995,0.3142857142857143,0.20232769620294389,0.584402332361516,0.3489871366097425,0.24268590817987387
4
+ -1,-1,0.46938775510204084,0.6530612244897959,0.8163265306122449,0.9591836734693877,0.46938775510204084,0.03304169886606065,0.4081632653061224,0.08663742657609082,0.3877551020408163,0.13074375193904886,0.34285714285714286,0.2206088169640079,0.6090055069646906,0.38115064093925494,0.2635297595122428
NanoBEIR_evaluation_mean_results.csv CHANGED
@@ -1,3 +1,4 @@
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.4053375196232339,0.601287284144427,0.6737519623233909,0.7369230769230769,0.4053375196232339,0.23516034838101724,0.26838304552590264,0.37175942432349296,0.20895447409733128,0.43675267025234743,0.1428226059654631,0.4908354981821823,0.5156608233036803,0.45145275407225244,0.3820046351353431
3
  -1,-1,0.35601255886970173,0.4918681318681318,0.5551334379905808,0.6368288854003141,0.35601255886970173,0.19193085732170106,0.2154788069073783,0.28067458983568583,0.17009105180533754,0.32547482072005907,0.12263736263736262,0.4004836172010528,0.44150164461388947,0.3695082615703847,0.30671940238397766
 
 
1
  epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
2
  -1,-1,0.4053375196232339,0.601287284144427,0.6737519623233909,0.7369230769230769,0.4053375196232339,0.23516034838101724,0.26838304552590264,0.37175942432349296,0.20895447409733128,0.43675267025234743,0.1428226059654631,0.4908354981821823,0.5156608233036803,0.45145275407225244,0.3820046351353431
3
  -1,-1,0.35601255886970173,0.4918681318681318,0.5551334379905808,0.6368288854003141,0.35601255886970173,0.19193085732170106,0.2154788069073783,0.28067458983568583,0.17009105180533754,0.32547482072005907,0.12263736263736262,0.4004836172010528,0.44150164461388947,0.3695082615703847,0.30671940238397766
4
+ -1,-1,0.35149136577708007,0.4902354788069073,0.5658712715855574,0.6491679748822605,0.35149136577708007,0.18446485464636025,0.2257561486132915,0.28725844278832385,0.18121193092621668,0.34314132490039767,0.1285274725274725,0.41258506430111763,0.44353216964441444,0.37688675285510337,0.3106340488088058
config.json CHANGED
@@ -1,25 +1,45 @@
1
  {
2
  "architectures": [
3
- "BertModel"
4
  ],
5
- "attention_probs_dropout_prob": 0.1,
6
- "classifier_dropout": null,
 
 
 
 
 
 
 
 
7
  "dtype": "float32",
 
 
 
 
8
  "gradient_checkpointing": false,
9
- "hidden_act": "gelu",
10
- "hidden_dropout_prob": 0.1,
11
- "hidden_size": 384,
12
  "initializer_range": 0.02,
13
- "intermediate_size": 1536,
14
- "layer_norm_eps": 1e-12,
15
- "max_position_embeddings": 512,
16
- "model_type": "bert",
 
 
 
 
 
 
17
  "num_attention_heads": 12,
18
- "num_hidden_layers": 12,
19
- "pad_token_id": 0,
20
  "position_embedding_type": "absolute",
 
 
 
 
21
  "transformers_version": "4.57.3",
22
- "type_vocab_size": 2,
23
- "use_cache": true,
24
- "vocab_size": 30522
25
  }
 
1
  {
2
  "architectures": [
3
+ "ModernBertModel"
4
  ],
5
+ "attention_bias": false,
6
+ "attention_dropout": 0.0,
7
+ "bos_token_id": 50281,
8
+ "classifier_activation": "gelu",
9
+ "classifier_bias": false,
10
+ "classifier_dropout": 0.0,
11
+ "classifier_pooling": "mean",
12
+ "cls_token_id": 50281,
13
+ "decoder_bias": true,
14
+ "deterministic_flash_attn": false,
15
  "dtype": "float32",
16
+ "embedding_dropout": 0.0,
17
+ "eos_token_id": 50282,
18
+ "global_attn_every_n_layers": 3,
19
+ "global_rope_theta": 160000.0,
20
  "gradient_checkpointing": false,
21
+ "hidden_activation": "gelu",
22
+ "hidden_size": 768,
23
+ "initializer_cutoff_factor": 2.0,
24
  "initializer_range": 0.02,
25
+ "intermediate_size": 1152,
26
+ "layer_norm_eps": 1e-05,
27
+ "local_attention": 128,
28
+ "local_rope_theta": 10000.0,
29
+ "max_position_embeddings": 8192,
30
+ "mlp_bias": false,
31
+ "mlp_dropout": 0.0,
32
+ "model_type": "modernbert",
33
+ "norm_bias": false,
34
+ "norm_eps": 1e-05,
35
  "num_attention_heads": 12,
36
+ "num_hidden_layers": 22,
37
+ "pad_token_id": 50283,
38
  "position_embedding_type": "absolute",
39
+ "repad_logits_with_grad": false,
40
+ "sep_token_id": 50282,
41
+ "sparse_pred_ignore_index": -100,
42
+ "sparse_prediction": false,
43
  "transformers_version": "4.57.3",
44
+ "vocab_size": 50368
 
 
45
  }
eval/Information-Retrieval_evaluation_NanoMSMARCO_results.csv CHANGED
@@ -46,3 +46,16 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
46
  2.873563218390805,2500,0.24,0.42,0.54,0.64,0.24,0.24,0.13999999999999999,0.42,0.10800000000000003,0.54,0.06400000000000002,0.64,0.36691269841269836,0.432368899073114,0.38007343445256936
47
  3.160919540229885,2750,0.24,0.42,0.54,0.64,0.24,0.24,0.13999999999999999,0.42,0.10800000000000003,0.54,0.06400000000000002,0.64,0.3633571428571428,0.42951100061476294,0.37648069668489414
48
  3.4482758620689653,3000,0.22,0.42,0.56,0.64,0.22,0.22,0.13999999999999999,0.42,0.11200000000000002,0.56,0.06400000000000002,0.64,0.3573571428571428,0.4253611031601517,0.37029891648053065
 
 
 
 
 
 
 
 
 
 
 
 
 
 
46
  2.873563218390805,2500,0.24,0.42,0.54,0.64,0.24,0.24,0.13999999999999999,0.42,0.10800000000000003,0.54,0.06400000000000002,0.64,0.36691269841269836,0.432368899073114,0.38007343445256936
47
  3.160919540229885,2750,0.24,0.42,0.54,0.64,0.24,0.24,0.13999999999999999,0.42,0.10800000000000003,0.54,0.06400000000000002,0.64,0.3633571428571428,0.42951100061476294,0.37648069668489414
48
  3.4482758620689653,3000,0.22,0.42,0.56,0.64,0.22,0.22,0.13999999999999999,0.42,0.11200000000000002,0.56,0.06400000000000002,0.64,0.3573571428571428,0.4253611031601517,0.37029891648053065
49
+ 0,0,0.44,0.72,0.76,0.86,0.44,0.44,0.24,0.72,0.15200000000000002,0.76,0.08599999999999998,0.86,0.5872222222222222,0.6530251712549636,0.5942230199326107
50
+ 0.28735632183908044,250,0.4,0.66,0.7,0.72,0.4,0.4,0.22,0.66,0.14,0.7,0.07200000000000001,0.72,0.5261904761904762,0.5748424895610357,0.5390199461547135
51
+ 0.5747126436781609,500,0.34,0.66,0.72,0.72,0.34,0.34,0.22,0.66,0.14400000000000002,0.72,0.07200000000000001,0.72,0.49633333333333324,0.5528921892365702,0.5066488350545559
52
+ 0.8620689655172413,750,0.42,0.62,0.66,0.72,0.42,0.42,0.20666666666666667,0.62,0.132,0.66,0.07200000000000001,0.72,0.5276666666666667,0.5747103368168414,0.5359588112757272
53
+ 1.1494252873563218,1000,0.4,0.6,0.62,0.7,0.4,0.4,0.2,0.6,0.12400000000000003,0.62,0.07,0.7,0.4998888888888889,0.5478691180843324,0.5101520097467759
54
+ 1.4367816091954024,1250,0.38,0.5,0.54,0.58,0.38,0.38,0.16666666666666663,0.5,0.10800000000000001,0.54,0.05800000000000001,0.58,0.44800000000000006,0.4801967800594191,0.4645675775637576
55
+ 1.7241379310344827,1500,0.4,0.46,0.5,0.56,0.4,0.4,0.1533333333333333,0.46,0.10000000000000002,0.5,0.05600000000000001,0.56,0.44211111111111107,0.46941027380193406,0.4532111240326796
56
+ 2.0114942528735633,1750,0.36,0.48,0.48,0.5,0.36,0.36,0.15999999999999998,0.48,0.096,0.48,0.05000000000000001,0.5,0.41952380952380947,0.4397596420238124,0.4296678787033921
57
+ 2.2988505747126435,2000,0.26,0.4,0.42,0.48,0.26,0.26,0.13333333333333333,0.4,0.084,0.42,0.04800000000000001,0.48,0.3354126984126984,0.37017506962491764,0.3450307545515735
58
+ 2.586206896551724,2250,0.28,0.42,0.44,0.58,0.28,0.28,0.13999999999999999,0.42,0.08800000000000001,0.44,0.05800000000000001,0.58,0.3686349206349206,0.4179673736035281,0.3785842002026509
59
+ 2.873563218390805,2500,0.22,0.38,0.42,0.54,0.22,0.22,0.12666666666666665,0.38,0.084,0.42,0.054000000000000006,0.54,0.3154682539682539,0.3687090141765658,0.3262437401648364
60
+ 3.160919540229885,2750,0.18,0.3,0.32,0.42,0.18,0.18,0.09999999999999998,0.3,0.064,0.32,0.04200000000000001,0.42,0.25072222222222224,0.29057091789008027,0.2613684398693639
61
+ 3.4482758620689653,3000,0.16,0.3,0.32,0.4,0.16,0.16,0.09999999999999998,0.3,0.064,0.32,0.04000000000000001,0.4,0.24177777777777776,0.2797381138841459,0.25452652172848145
eval/Information-Retrieval_evaluation_NanoNQ_results.csv CHANGED
@@ -46,3 +46,16 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
46
  2.873563218390805,2500,0.18,0.34,0.4,0.48,0.18,0.16,0.11333333333333333,0.32,0.08,0.37,0.04800000000000001,0.45,0.2776349206349206,0.3072350459331644,0.2695566560468123
47
  3.160919540229885,2750,0.18,0.32,0.4,0.48,0.18,0.16,0.10666666666666666,0.3,0.08,0.37,0.04800000000000001,0.45,0.27311111111111114,0.303687459098697,0.2643930056155039
48
  3.4482758620689653,3000,0.18,0.34,0.4,0.48,0.18,0.16,0.11333333333333333,0.32,0.08,0.37,0.04800000000000001,0.45,0.27455555555555555,0.30483462455030724,0.26647869540792385
 
 
 
 
 
 
 
 
 
 
 
 
 
 
46
  2.873563218390805,2500,0.18,0.34,0.4,0.48,0.18,0.16,0.11333333333333333,0.32,0.08,0.37,0.04800000000000001,0.45,0.2776349206349206,0.3072350459331644,0.2695566560468123
47
  3.160919540229885,2750,0.18,0.32,0.4,0.48,0.18,0.16,0.10666666666666666,0.3,0.08,0.37,0.04800000000000001,0.45,0.27311111111111114,0.303687459098697,0.2643930056155039
48
  3.4482758620689653,3000,0.18,0.34,0.4,0.48,0.18,0.16,0.11333333333333333,0.32,0.08,0.37,0.04800000000000001,0.45,0.27455555555555555,0.30483462455030724,0.26647869540792385
49
+ 0,0,0.52,0.7,0.78,0.84,0.52,0.49,0.2333333333333333,0.65,0.15600000000000003,0.73,0.08999999999999998,0.8,0.6295238095238095,0.655180139603386,0.6050874426120327
50
+ 0.28735632183908044,250,0.54,0.6,0.7,0.8,0.54,0.5,0.20666666666666664,0.57,0.14400000000000002,0.65,0.08399999999999999,0.75,0.6070238095238095,0.6238817517972675,0.5823155072745749
51
+ 0.5747126436781609,500,0.44,0.6,0.68,0.74,0.44,0.41,0.20666666666666664,0.55,0.14400000000000002,0.64,0.07800000000000001,0.69,0.5353015873015873,0.558348574721249,0.51659168738929
52
+ 0.8620689655172413,750,0.34,0.42,0.48,0.58,0.34,0.31,0.14666666666666667,0.39,0.1,0.45,0.064,0.56,0.4017777777777778,0.42985614779615433,0.39131509074550686
53
+ 1.1494252873563218,1000,0.42,0.48,0.52,0.56,0.42,0.37,0.1733333333333333,0.45,0.11199999999999999,0.49,0.062,0.54,0.4651904761904762,0.4668719442137559,0.4471411851134015
54
+ 1.4367816091954024,1250,0.3,0.46,0.54,0.58,0.3,0.26,0.16666666666666663,0.43,0.11599999999999999,0.51,0.066,0.56,0.3907460317460318,0.4214181619624209,0.37472392739454635
55
+ 1.7241379310344827,1500,0.3,0.38,0.42,0.46,0.3,0.26,0.13999999999999999,0.35,0.09200000000000001,0.38,0.05200000000000001,0.43,0.3475555555555555,0.35466597693106505,0.33110189519216443
56
+ 2.0114942528735633,1750,0.2,0.3,0.32,0.4,0.2,0.17,0.10666666666666666,0.27,0.068,0.29,0.044000000000000004,0.38,0.2558888888888889,0.27230781853149144,0.2394314014202172
57
+ 2.2988505747126435,2000,0.12,0.24,0.26,0.34,0.12,0.12,0.07999999999999999,0.22,0.05200000000000001,0.23,0.034,0.31,0.19119047619047616,0.21435273721601938,0.188482017982018
58
+ 2.586206896551724,2250,0.14,0.34,0.4,0.4,0.14,0.12,0.11333333333333333,0.3,0.08,0.35,0.042,0.36,0.2406666666666667,0.2574874896340833,0.22243671984298377
59
+ 2.873563218390805,2500,0.18,0.26,0.34,0.44,0.18,0.15,0.08666666666666666,0.23,0.068,0.3,0.046000000000000006,0.4,0.24624603174603174,0.26616251509536853,0.2197416495436074
60
+ 3.160919540229885,2750,0.1,0.12,0.16,0.22,0.1,0.08,0.04,0.09,0.032,0.13,0.022000000000000002,0.19,0.12721428571428572,0.12825616203051576,0.11071657644805219
61
+ 3.4482758620689653,3000,0.1,0.12,0.16,0.26,0.1,0.08,0.04,0.09,0.032,0.13,0.026000000000000002,0.23,0.12794444444444442,0.13826388457522362,0.10725400911912068
eval/NanoBEIR_evaluation_mean_results.csv CHANGED
@@ -46,3 +46,16 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
46
  2.873563218390805,2500,0.21,0.38,0.47000000000000003,0.56,0.21,0.2,0.12666666666666665,0.37,0.09400000000000001,0.455,0.05600000000000001,0.545,0.32227380952380946,0.3698019725031392,0.32481504524969085
47
  3.160919540229885,2750,0.21,0.37,0.47000000000000003,0.56,0.21,0.2,0.12333333333333332,0.36,0.09400000000000001,0.455,0.05600000000000001,0.545,0.318234126984127,0.36659922985673,0.32043685115019904
48
  3.4482758620689653,3000,0.2,0.38,0.48000000000000004,0.56,0.2,0.19,0.12666666666666665,0.37,0.096,0.465,0.05600000000000001,0.545,0.3159563492063492,0.36509786385522947,0.31838880594422725
 
 
 
 
 
 
 
 
 
 
 
 
 
 
46
  2.873563218390805,2500,0.21,0.38,0.47000000000000003,0.56,0.21,0.2,0.12666666666666665,0.37,0.09400000000000001,0.455,0.05600000000000001,0.545,0.32227380952380946,0.3698019725031392,0.32481504524969085
47
  3.160919540229885,2750,0.21,0.37,0.47000000000000003,0.56,0.21,0.2,0.12333333333333332,0.36,0.09400000000000001,0.455,0.05600000000000001,0.545,0.318234126984127,0.36659922985673,0.32043685115019904
48
  3.4482758620689653,3000,0.2,0.38,0.48000000000000004,0.56,0.2,0.19,0.12666666666666665,0.37,0.096,0.465,0.05600000000000001,0.545,0.3159563492063492,0.36509786385522947,0.31838880594422725
49
+ 0,0,0.48,0.71,0.77,0.85,0.48,0.46499999999999997,0.23666666666666664,0.685,0.15400000000000003,0.745,0.08799999999999998,0.8300000000000001,0.6083730158730158,0.6541026554291748,0.5996552312723218
50
+ 0.28735632183908044,250,0.47000000000000003,0.63,0.7,0.76,0.47000000000000003,0.45,0.21333333333333332,0.615,0.14200000000000002,0.675,0.078,0.735,0.5666071428571429,0.5993621206791515,0.5606677267146443
51
+ 0.5747126436781609,500,0.39,0.63,0.7,0.73,0.39,0.375,0.21333333333333332,0.605,0.14400000000000002,0.6799999999999999,0.07500000000000001,0.705,0.5158174603174602,0.5556203819789096,0.511620261221923
52
+ 0.8620689655172413,750,0.38,0.52,0.5700000000000001,0.6499999999999999,0.38,0.365,0.17666666666666667,0.505,0.116,0.555,0.068,0.64,0.46472222222222226,0.5022832423064978,0.463636951010617
53
+ 1.1494252873563218,1000,0.41000000000000003,0.54,0.5700000000000001,0.63,0.41000000000000003,0.385,0.18666666666666665,0.525,0.11800000000000001,0.5549999999999999,0.066,0.62,0.48253968253968255,0.5073705311490442,0.4786465974300887
54
+ 1.4367816091954024,1250,0.33999999999999997,0.48,0.54,0.58,0.33999999999999997,0.32,0.16666666666666663,0.46499999999999997,0.112,0.525,0.062000000000000006,0.5700000000000001,0.4193730158730159,0.45080747101092,0.419645752479152
55
+ 1.7241379310344827,1500,0.35,0.42000000000000004,0.45999999999999996,0.51,0.35,0.33,0.14666666666666664,0.405,0.09600000000000002,0.44,0.054000000000000006,0.495,0.39483333333333326,0.41203812536649953,0.392156509612422
56
+ 2.0114942528735633,1750,0.28,0.39,0.4,0.45,0.28,0.265,0.1333333333333333,0.375,0.082,0.385,0.04700000000000001,0.44,0.3377063492063492,0.35603373027765195,0.33454964006180465
57
+ 2.2988505747126435,2000,0.19,0.32,0.33999999999999997,0.41000000000000003,0.19,0.19,0.10666666666666666,0.31,0.068,0.325,0.04100000000000001,0.395,0.26330158730158726,0.2922639034204685,0.26675638626679576
58
+ 2.586206896551724,2250,0.21000000000000002,0.38,0.42000000000000004,0.49,0.21000000000000002,0.2,0.12666666666666665,0.36,0.084,0.395,0.05,0.47,0.3046507936507936,0.3377274316188057,0.30051046002281734
59
+ 2.873563218390805,2500,0.2,0.32,0.38,0.49,0.2,0.185,0.10666666666666666,0.305,0.07600000000000001,0.36,0.05,0.47000000000000003,0.2808571428571428,0.3174357646359672,0.2729926948542219
60
+ 3.160919540229885,2750,0.14,0.21,0.24,0.32,0.14,0.13,0.06999999999999999,0.195,0.048,0.225,0.03200000000000001,0.305,0.18896825396825398,0.20941353996029802,0.18604250815870804
61
+ 3.4482758620689653,3000,0.13,0.21,0.24,0.33,0.13,0.12,0.06999999999999999,0.195,0.048,0.225,0.033,0.315,0.1848611111111111,0.20900099922968474,0.18089026542380107
final_metrics.json CHANGED
@@ -1,231 +1,231 @@
1
  {
2
  "nano_beir": {
3
- "NanoClimateFEVER_cosine_accuracy@1": 0.14,
4
- "NanoClimateFEVER_cosine_accuracy@3": 0.22,
5
- "NanoClimateFEVER_cosine_accuracy@5": 0.26,
6
- "NanoClimateFEVER_cosine_accuracy@10": 0.38,
7
- "NanoClimateFEVER_cosine_precision@1": 0.14,
8
- "NanoClimateFEVER_cosine_precision@3": 0.07333333333333333,
9
- "NanoClimateFEVER_cosine_precision@5": 0.05200000000000001,
10
- "NanoClimateFEVER_cosine_precision@10": 0.038,
11
- "NanoClimateFEVER_cosine_recall@1": 0.07,
12
- "NanoClimateFEVER_cosine_recall@3": 0.11066666666666666,
13
- "NanoClimateFEVER_cosine_recall@5": 0.13566666666666666,
14
- "NanoClimateFEVER_cosine_recall@10": 0.19066666666666665,
15
- "NanoClimateFEVER_cosine_ndcg@10": 0.1453885297185151,
16
- "NanoClimateFEVER_cosine_mrr@10": 0.20153968253968252,
17
- "NanoClimateFEVER_cosine_map@100": 0.10907272614067173,
18
- "NanoDBPedia_cosine_accuracy@1": 0.52,
19
- "NanoDBPedia_cosine_accuracy@3": 0.72,
20
- "NanoDBPedia_cosine_accuracy@5": 0.82,
21
- "NanoDBPedia_cosine_accuracy@10": 0.86,
22
- "NanoDBPedia_cosine_precision@1": 0.52,
23
- "NanoDBPedia_cosine_precision@3": 0.4,
24
- "NanoDBPedia_cosine_precision@5": 0.364,
25
- "NanoDBPedia_cosine_precision@10": 0.30000000000000004,
26
- "NanoDBPedia_cosine_recall@1": 0.047202979496018524,
27
- "NanoDBPedia_cosine_recall@3": 0.10194727189869665,
28
- "NanoDBPedia_cosine_recall@5": 0.15730653946206946,
29
- "NanoDBPedia_cosine_recall@10": 0.22246963483004237,
30
- "NanoDBPedia_cosine_ndcg@10": 0.38619002202024644,
31
- "NanoDBPedia_cosine_mrr@10": 0.6298333333333334,
32
- "NanoDBPedia_cosine_map@100": 0.2319232549425231,
33
- "NanoFEVER_cosine_accuracy@1": 0.28,
34
- "NanoFEVER_cosine_accuracy@3": 0.52,
35
- "NanoFEVER_cosine_accuracy@5": 0.6,
36
- "NanoFEVER_cosine_accuracy@10": 0.68,
37
- "NanoFEVER_cosine_precision@1": 0.28,
38
- "NanoFEVER_cosine_precision@3": 0.1733333333333333,
39
- "NanoFEVER_cosine_precision@5": 0.12,
40
- "NanoFEVER_cosine_precision@10": 0.07,
41
- "NanoFEVER_cosine_recall@1": 0.27,
42
- "NanoFEVER_cosine_recall@3": 0.49,
43
- "NanoFEVER_cosine_recall@5": 0.57,
44
- "NanoFEVER_cosine_recall@10": 0.65,
45
- "NanoFEVER_cosine_ndcg@10": 0.4689004130810094,
46
- "NanoFEVER_cosine_mrr@10": 0.4225238095238095,
47
- "NanoFEVER_cosine_map@100": 0.4118080771584329,
48
- "NanoFiQA2018_cosine_accuracy@1": 0.26,
49
- "NanoFiQA2018_cosine_accuracy@3": 0.36,
50
- "NanoFiQA2018_cosine_accuracy@5": 0.4,
51
- "NanoFiQA2018_cosine_accuracy@10": 0.48,
52
- "NanoFiQA2018_cosine_precision@1": 0.26,
53
- "NanoFiQA2018_cosine_precision@3": 0.13999999999999999,
54
- "NanoFiQA2018_cosine_precision@5": 0.10000000000000002,
55
- "NanoFiQA2018_cosine_precision@10": 0.064,
56
- "NanoFiQA2018_cosine_recall@1": 0.1585238095238095,
57
- "NanoFiQA2018_cosine_recall@3": 0.2282698412698413,
58
- "NanoFiQA2018_cosine_recall@5": 0.2517936507936508,
59
- "NanoFiQA2018_cosine_recall@10": 0.3186825396825397,
60
- "NanoFiQA2018_cosine_ndcg@10": 0.26876133900480464,
61
- "NanoFiQA2018_cosine_mrr@10": 0.3242460317460317,
62
- "NanoFiQA2018_cosine_map@100": 0.24128551555161426,
63
- "NanoHotpotQA_cosine_accuracy@1": 0.54,
64
- "NanoHotpotQA_cosine_accuracy@3": 0.66,
65
  "NanoHotpotQA_cosine_accuracy@5": 0.74,
66
- "NanoHotpotQA_cosine_accuracy@10": 0.84,
67
- "NanoHotpotQA_cosine_precision@1": 0.54,
68
- "NanoHotpotQA_cosine_precision@3": 0.2533333333333333,
69
- "NanoHotpotQA_cosine_precision@5": 0.17600000000000002,
70
- "NanoHotpotQA_cosine_precision@10": 0.10599999999999998,
71
- "NanoHotpotQA_cosine_recall@1": 0.27,
72
- "NanoHotpotQA_cosine_recall@3": 0.38,
73
- "NanoHotpotQA_cosine_recall@5": 0.44,
74
- "NanoHotpotQA_cosine_recall@10": 0.53,
75
- "NanoHotpotQA_cosine_ndcg@10": 0.4749742091237649,
76
- "NanoHotpotQA_cosine_mrr@10": 0.6256031746031746,
77
- "NanoHotpotQA_cosine_map@100": 0.38794691370738704,
78
- "NanoMSMARCO_cosine_accuracy@1": 0.28,
79
- "NanoMSMARCO_cosine_accuracy@3": 0.38,
80
- "NanoMSMARCO_cosine_accuracy@5": 0.42,
81
- "NanoMSMARCO_cosine_accuracy@10": 0.56,
82
- "NanoMSMARCO_cosine_precision@1": 0.28,
83
- "NanoMSMARCO_cosine_precision@3": 0.12666666666666665,
84
- "NanoMSMARCO_cosine_precision@5": 0.084,
85
- "NanoMSMARCO_cosine_precision@10": 0.05600000000000001,
86
- "NanoMSMARCO_cosine_recall@1": 0.28,
87
- "NanoMSMARCO_cosine_recall@3": 0.38,
88
- "NanoMSMARCO_cosine_recall@5": 0.42,
89
- "NanoMSMARCO_cosine_recall@10": 0.56,
90
- "NanoMSMARCO_cosine_ndcg@10": 0.4001173610020243,
91
- "NanoMSMARCO_cosine_mrr@10": 0.3516904761904761,
92
- "NanoMSMARCO_cosine_map@100": 0.37336992686291426,
93
- "NanoNFCorpus_cosine_accuracy@1": 0.36,
94
  "NanoNFCorpus_cosine_accuracy@3": 0.46,
95
- "NanoNFCorpus_cosine_accuracy@5": 0.5,
96
- "NanoNFCorpus_cosine_accuracy@10": 0.56,
97
- "NanoNFCorpus_cosine_precision@1": 0.36,
98
- "NanoNFCorpus_cosine_precision@3": 0.2733333333333333,
99
- "NanoNFCorpus_cosine_precision@5": 0.256,
100
- "NanoNFCorpus_cosine_precision@10": 0.21799999999999997,
101
- "NanoNFCorpus_cosine_recall@1": 0.01309333347305052,
102
- "NanoNFCorpus_cosine_recall@3": 0.029796345008688278,
103
- "NanoNFCorpus_cosine_recall@5": 0.04461630481223397,
104
- "NanoNFCorpus_cosine_recall@10": 0.06880715289816099,
105
- "NanoNFCorpus_cosine_ndcg@10": 0.24206789327168107,
106
- "NanoNFCorpus_cosine_mrr@10": 0.4221111111111111,
107
- "NanoNFCorpus_cosine_map@100": 0.08443685448289194,
108
- "NanoNQ_cosine_accuracy@1": 0.24,
109
- "NanoNQ_cosine_accuracy@3": 0.32,
110
- "NanoNQ_cosine_accuracy@5": 0.38,
111
- "NanoNQ_cosine_accuracy@10": 0.44,
112
- "NanoNQ_cosine_precision@1": 0.24,
113
- "NanoNQ_cosine_precision@3": 0.10666666666666665,
114
- "NanoNQ_cosine_precision@5": 0.07600000000000001,
115
- "NanoNQ_cosine_precision@10": 0.046,
116
- "NanoNQ_cosine_recall@1": 0.23,
117
- "NanoNQ_cosine_recall@3": 0.3,
118
- "NanoNQ_cosine_recall@5": 0.35,
119
- "NanoNQ_cosine_recall@10": 0.42,
120
- "NanoNQ_cosine_ndcg@10": 0.32272214750507383,
121
- "NanoNQ_cosine_mrr@10": 0.30133333333333334,
122
- "NanoNQ_cosine_map@100": 0.3026672483997021,
123
- "NanoQuoraRetrieval_cosine_accuracy@1": 0.94,
124
  "NanoQuoraRetrieval_cosine_accuracy@3": 0.98,
125
  "NanoQuoraRetrieval_cosine_accuracy@5": 1.0,
126
  "NanoQuoraRetrieval_cosine_accuracy@10": 1.0,
127
- "NanoQuoraRetrieval_cosine_precision@1": 0.94,
128
- "NanoQuoraRetrieval_cosine_precision@3": 0.40666666666666657,
129
- "NanoQuoraRetrieval_cosine_precision@5": 0.264,
130
- "NanoQuoraRetrieval_cosine_precision@10": 0.13799999999999998,
131
- "NanoQuoraRetrieval_cosine_recall@1": 0.8273333333333334,
132
- "NanoQuoraRetrieval_cosine_recall@3": 0.9453333333333334,
133
- "NanoQuoraRetrieval_cosine_recall@5": 0.986,
134
- "NanoQuoraRetrieval_cosine_recall@10": 0.9966666666666666,
135
- "NanoQuoraRetrieval_cosine_ndcg@10": 0.9649140578691123,
136
- "NanoQuoraRetrieval_cosine_mrr@10": 0.9616666666666667,
137
- "NanoQuoraRetrieval_cosine_map@100": 0.9493650793650792,
138
- "NanoSCIDOCS_cosine_accuracy@1": 0.42,
139
- "NanoSCIDOCS_cosine_accuracy@3": 0.6,
140
- "NanoSCIDOCS_cosine_accuracy@5": 0.72,
141
- "NanoSCIDOCS_cosine_accuracy@10": 0.8,
142
- "NanoSCIDOCS_cosine_precision@1": 0.42,
143
- "NanoSCIDOCS_cosine_precision@3": 0.2933333333333333,
144
- "NanoSCIDOCS_cosine_precision@5": 0.24800000000000005,
145
- "NanoSCIDOCS_cosine_precision@10": 0.16399999999999998,
146
- "NanoSCIDOCS_cosine_recall@1": 0.08700000000000001,
147
- "NanoSCIDOCS_cosine_recall@3": 0.18100000000000002,
148
- "NanoSCIDOCS_cosine_recall@5": 0.25666666666666665,
149
- "NanoSCIDOCS_cosine_recall@10": 0.33666666666666656,
150
- "NanoSCIDOCS_cosine_ndcg@10": 0.3309587311349605,
151
- "NanoSCIDOCS_cosine_mrr@10": 0.5280555555555556,
152
- "NanoSCIDOCS_cosine_map@100": 0.2571164275500479,
153
- "NanoArguAna_cosine_accuracy@1": 0.04,
154
  "NanoArguAna_cosine_accuracy@3": 0.18,
155
- "NanoArguAna_cosine_accuracy@5": 0.2,
156
  "NanoArguAna_cosine_accuracy@10": 0.34,
157
- "NanoArguAna_cosine_precision@1": 0.04,
158
  "NanoArguAna_cosine_precision@3": 0.06,
159
- "NanoArguAna_cosine_precision@5": 0.04,
160
  "NanoArguAna_cosine_precision@10": 0.034,
161
- "NanoArguAna_cosine_recall@1": 0.04,
162
  "NanoArguAna_cosine_recall@3": 0.18,
163
- "NanoArguAna_cosine_recall@5": 0.2,
164
  "NanoArguAna_cosine_recall@10": 0.34,
165
- "NanoArguAna_cosine_ndcg@10": 0.175419302465962,
166
- "NanoArguAna_cosine_mrr@10": 0.12532539682539678,
167
- "NanoArguAna_cosine_map@100": 0.14459756648011524,
168
- "NanoSciFact_cosine_accuracy@1": 0.2,
169
- "NanoSciFact_cosine_accuracy@3": 0.28,
170
- "NanoSciFact_cosine_accuracy@5": 0.34,
171
- "NanoSciFact_cosine_accuracy@10": 0.4,
172
- "NanoSciFact_cosine_precision@1": 0.2,
173
- "NanoSciFact_cosine_precision@3": 0.1,
174
- "NanoSciFact_cosine_precision@5": 0.07200000000000001,
175
- "NanoSciFact_cosine_precision@10": 0.046000000000000006,
176
- "NanoSciFact_cosine_recall@1": 0.175,
177
- "NanoSciFact_cosine_recall@3": 0.24,
178
- "NanoSciFact_cosine_recall@5": 0.3,
179
- "NanoSciFact_cosine_recall@10": 0.37,
180
- "NanoSciFact_cosine_ndcg@10": 0.2742062576081037,
181
- "NanoSciFact_cosine_mrr@10": 0.2611904761904762,
182
- "NanoSciFact_cosine_map@100": 0.25107673217045623,
183
- "NanoTouche2020_cosine_accuracy@1": 0.40816326530612246,
184
- "NanoTouche2020_cosine_accuracy@3": 0.7142857142857143,
185
- "NanoTouche2020_cosine_accuracy@5": 0.8367346938775511,
186
- "NanoTouche2020_cosine_accuracy@10": 0.9387755102040817,
187
- "NanoTouche2020_cosine_precision@1": 0.40816326530612246,
188
- "NanoTouche2020_cosine_precision@3": 0.3945578231292517,
189
- "NanoTouche2020_cosine_precision@5": 0.3591836734693878,
190
- "NanoTouche2020_cosine_precision@10": 0.3142857142857143,
191
- "NanoTouche2020_cosine_recall@1": 0.026947689355902065,
192
- "NanoTouche2020_cosine_recall@3": 0.08175620968668966,
193
- "NanoTouche2020_cosine_recall@5": 0.11912284095947995,
194
- "NanoTouche2020_cosine_recall@10": 0.20232769620294389,
195
- "NanoTouche2020_cosine_ndcg@10": 0.3489871366097425,
196
- "NanoTouche2020_cosine_mrr@10": 0.584402332361516,
197
- "NanoTouche2020_cosine_map@100": 0.24268590817987387,
198
- "NanoBEIR_mean_cosine_accuracy@1": 0.35601255886970173,
199
- "NanoBEIR_mean_cosine_accuracy@3": 0.4918681318681318,
200
- "NanoBEIR_mean_cosine_accuracy@5": 0.5551334379905808,
201
- "NanoBEIR_mean_cosine_accuracy@10": 0.6368288854003141,
202
- "NanoBEIR_mean_cosine_precision@1": 0.35601255886970173,
203
- "NanoBEIR_mean_cosine_precision@3": 0.2154788069073783,
204
- "NanoBEIR_mean_cosine_precision@5": 0.17009105180533754,
205
- "NanoBEIR_mean_cosine_precision@10": 0.12263736263736262,
206
- "NanoBEIR_mean_cosine_recall@1": 0.19193085732170106,
207
- "NanoBEIR_mean_cosine_recall@3": 0.28067458983568583,
208
- "NanoBEIR_mean_cosine_recall@5": 0.32547482072005907,
209
- "NanoBEIR_mean_cosine_recall@10": 0.4004836172010528,
210
- "NanoBEIR_mean_cosine_ndcg@10": 0.3695082615703847,
211
- "NanoBEIR_mean_cosine_mrr@10": 0.44150164461388947,
212
- "NanoBEIR_mean_cosine_map@100": 0.30671940238397766
213
  },
214
  "beir_touche2020": {
215
- "BeIR-touche2020-subset-test_cosine_accuracy@1": 0.7142857142857143,
216
- "BeIR-touche2020-subset-test_cosine_accuracy@3": 0.8979591836734694,
217
  "BeIR-touche2020-subset-test_cosine_accuracy@5": 0.9387755102040817,
218
- "BeIR-touche2020-subset-test_cosine_accuracy@10": 0.9795918367346939,
219
- "BeIR-touche2020-subset-test_cosine_precision@1": 0.7142857142857143,
220
- "BeIR-touche2020-subset-test_cosine_precision@3": 0.6802721088435375,
221
  "BeIR-touche2020-subset-test_cosine_precision@5": 0.6204081632653061,
222
- "BeIR-touche2020-subset-test_cosine_precision@10": 0.5469387755102041,
223
- "BeIR-touche2020-subset-test_cosine_recall@1": 0.015888088527206596,
224
- "BeIR-touche2020-subset-test_cosine_recall@3": 0.04529851299481363,
225
- "BeIR-touche2020-subset-test_cosine_recall@5": 0.06854028378310305,
226
- "BeIR-touche2020-subset-test_cosine_recall@10": 0.12037980510830988,
227
- "BeIR-touche2020-subset-test_cosine_ndcg@10": 0.5854787058529846,
228
- "BeIR-touche2020-subset-test_cosine_mrr@10": 0.8197278911564625,
229
- "BeIR-touche2020-subset-test_cosine_map@100": 0.2463904322921895
230
  }
231
  }
 
1
  {
2
  "nano_beir": {
3
+ "NanoClimateFEVER_cosine_accuracy@1": 0.1,
4
+ "NanoClimateFEVER_cosine_accuracy@3": 0.16,
5
+ "NanoClimateFEVER_cosine_accuracy@5": 0.18,
6
+ "NanoClimateFEVER_cosine_accuracy@10": 0.36,
7
+ "NanoClimateFEVER_cosine_precision@1": 0.1,
8
+ "NanoClimateFEVER_cosine_precision@3": 0.05333333333333333,
9
+ "NanoClimateFEVER_cosine_precision@5": 0.04,
10
+ "NanoClimateFEVER_cosine_precision@10": 0.038000000000000006,
11
+ "NanoClimateFEVER_cosine_recall@1": 0.039,
12
+ "NanoClimateFEVER_cosine_recall@3": 0.07233333333333332,
13
+ "NanoClimateFEVER_cosine_recall@5": 0.09899999999999999,
14
+ "NanoClimateFEVER_cosine_recall@10": 0.17800000000000002,
15
+ "NanoClimateFEVER_cosine_ndcg@10": 0.1173759125527998,
16
+ "NanoClimateFEVER_cosine_mrr@10": 0.15424603174603174,
17
+ "NanoClimateFEVER_cosine_map@100": 0.08470650399139114,
18
+ "NanoDBPedia_cosine_accuracy@1": 0.54,
19
+ "NanoDBPedia_cosine_accuracy@3": 0.76,
20
+ "NanoDBPedia_cosine_accuracy@5": 0.84,
21
+ "NanoDBPedia_cosine_accuracy@10": 0.9,
22
+ "NanoDBPedia_cosine_precision@1": 0.54,
23
+ "NanoDBPedia_cosine_precision@3": 0.42,
24
+ "NanoDBPedia_cosine_precision@5": 0.384,
25
+ "NanoDBPedia_cosine_precision@10": 0.29200000000000004,
26
+ "NanoDBPedia_cosine_recall@1": 0.07619799906535789,
27
+ "NanoDBPedia_cosine_recall@3": 0.1276779058713768,
28
+ "NanoDBPedia_cosine_recall@5": 0.16749620234443643,
29
+ "NanoDBPedia_cosine_recall@10": 0.21087586592616692,
30
+ "NanoDBPedia_cosine_ndcg@10": 0.3969317585871071,
31
+ "NanoDBPedia_cosine_mrr@10": 0.6681666666666666,
32
+ "NanoDBPedia_cosine_map@100": 0.25479322904197393,
33
+ "NanoFEVER_cosine_accuracy@1": 0.3,
34
+ "NanoFEVER_cosine_accuracy@3": 0.44,
35
+ "NanoFEVER_cosine_accuracy@5": 0.52,
36
+ "NanoFEVER_cosine_accuracy@10": 0.58,
37
+ "NanoFEVER_cosine_precision@1": 0.3,
38
+ "NanoFEVER_cosine_precision@3": 0.14666666666666667,
39
+ "NanoFEVER_cosine_precision@5": 0.10800000000000001,
40
+ "NanoFEVER_cosine_precision@10": 0.062,
41
+ "NanoFEVER_cosine_recall@1": 0.28,
42
+ "NanoFEVER_cosine_recall@3": 0.41,
43
+ "NanoFEVER_cosine_recall@5": 0.5,
44
+ "NanoFEVER_cosine_recall@10": 0.56,
45
+ "NanoFEVER_cosine_ndcg@10": 0.4268388511477842,
46
+ "NanoFEVER_cosine_mrr@10": 0.39605555555555555,
47
+ "NanoFEVER_cosine_map@100": 0.3890457012149144,
48
+ "NanoFiQA2018_cosine_accuracy@1": 0.22,
49
+ "NanoFiQA2018_cosine_accuracy@3": 0.34,
50
+ "NanoFiQA2018_cosine_accuracy@5": 0.44,
51
+ "NanoFiQA2018_cosine_accuracy@10": 0.6,
52
+ "NanoFiQA2018_cosine_precision@1": 0.22,
53
+ "NanoFiQA2018_cosine_precision@3": 0.15333333333333332,
54
+ "NanoFiQA2018_cosine_precision@5": 0.124,
55
+ "NanoFiQA2018_cosine_precision@10": 0.094,
56
+ "NanoFiQA2018_cosine_recall@1": 0.11407936507936509,
57
+ "NanoFiQA2018_cosine_recall@3": 0.21912698412698411,
58
+ "NanoFiQA2018_cosine_recall@5": 0.2806825396825397,
59
+ "NanoFiQA2018_cosine_recall@10": 0.4115714285714286,
60
+ "NanoFiQA2018_cosine_ndcg@10": 0.29458681641245554,
61
+ "NanoFiQA2018_cosine_mrr@10": 0.3207142857142857,
62
+ "NanoFiQA2018_cosine_map@100": 0.23364616122992465,
63
+ "NanoHotpotQA_cosine_accuracy@1": 0.52,
64
+ "NanoHotpotQA_cosine_accuracy@3": 0.68,
65
  "NanoHotpotQA_cosine_accuracy@5": 0.74,
66
+ "NanoHotpotQA_cosine_accuracy@10": 0.78,
67
+ "NanoHotpotQA_cosine_precision@1": 0.52,
68
+ "NanoHotpotQA_cosine_precision@3": 0.2733333333333334,
69
+ "NanoHotpotQA_cosine_precision@5": 0.184,
70
+ "NanoHotpotQA_cosine_precision@10": 0.102,
71
+ "NanoHotpotQA_cosine_recall@1": 0.26,
72
+ "NanoHotpotQA_cosine_recall@3": 0.41,
73
+ "NanoHotpotQA_cosine_recall@5": 0.46,
74
+ "NanoHotpotQA_cosine_recall@10": 0.51,
75
+ "NanoHotpotQA_cosine_ndcg@10": 0.46561524553654626,
76
+ "NanoHotpotQA_cosine_mrr@10": 0.6083333333333334,
77
+ "NanoHotpotQA_cosine_map@100": 0.3863310446433211,
78
+ "NanoMSMARCO_cosine_accuracy@1": 0.22,
79
+ "NanoMSMARCO_cosine_accuracy@3": 0.42,
80
+ "NanoMSMARCO_cosine_accuracy@5": 0.56,
81
+ "NanoMSMARCO_cosine_accuracy@10": 0.64,
82
+ "NanoMSMARCO_cosine_precision@1": 0.22,
83
+ "NanoMSMARCO_cosine_precision@3": 0.13999999999999999,
84
+ "NanoMSMARCO_cosine_precision@5": 0.11200000000000002,
85
+ "NanoMSMARCO_cosine_precision@10": 0.06400000000000002,
86
+ "NanoMSMARCO_cosine_recall@1": 0.22,
87
+ "NanoMSMARCO_cosine_recall@3": 0.42,
88
+ "NanoMSMARCO_cosine_recall@5": 0.56,
89
+ "NanoMSMARCO_cosine_recall@10": 0.64,
90
+ "NanoMSMARCO_cosine_ndcg@10": 0.4253611031601517,
91
+ "NanoMSMARCO_cosine_mrr@10": 0.3573571428571428,
92
+ "NanoMSMARCO_cosine_map@100": 0.37029891648053065,
93
+ "NanoNFCorpus_cosine_accuracy@1": 0.32,
94
  "NanoNFCorpus_cosine_accuracy@3": 0.46,
95
+ "NanoNFCorpus_cosine_accuracy@5": 0.54,
96
+ "NanoNFCorpus_cosine_accuracy@10": 0.6,
97
+ "NanoNFCorpus_cosine_precision@1": 0.32,
98
+ "NanoNFCorpus_cosine_precision@3": 0.28,
99
+ "NanoNFCorpus_cosine_precision@5": 0.26,
100
+ "NanoNFCorpus_cosine_precision@10": 0.222,
101
+ "NanoNFCorpus_cosine_recall@1": 0.012390714058566699,
102
+ "NanoNFCorpus_cosine_recall@3": 0.03091743967375776,
103
+ "NanoNFCorpus_cosine_recall@5": 0.0669147297391448,
104
+ "NanoNFCorpus_cosine_recall@10": 0.09088305778625912,
105
+ "NanoNFCorpus_cosine_ndcg@10": 0.2483348722648785,
106
+ "NanoNFCorpus_cosine_mrr@10": 0.4105238095238095,
107
+ "NanoNFCorpus_cosine_map@100": 0.09280425392585814,
108
+ "NanoNQ_cosine_accuracy@1": 0.18,
109
+ "NanoNQ_cosine_accuracy@3": 0.34,
110
+ "NanoNQ_cosine_accuracy@5": 0.4,
111
+ "NanoNQ_cosine_accuracy@10": 0.48,
112
+ "NanoNQ_cosine_precision@1": 0.18,
113
+ "NanoNQ_cosine_precision@3": 0.11333333333333333,
114
+ "NanoNQ_cosine_precision@5": 0.08,
115
+ "NanoNQ_cosine_precision@10": 0.04800000000000001,
116
+ "NanoNQ_cosine_recall@1": 0.16,
117
+ "NanoNQ_cosine_recall@3": 0.32,
118
+ "NanoNQ_cosine_recall@5": 0.37,
119
+ "NanoNQ_cosine_recall@10": 0.45,
120
+ "NanoNQ_cosine_ndcg@10": 0.30483462455030724,
121
+ "NanoNQ_cosine_mrr@10": 0.27455555555555555,
122
+ "NanoNQ_cosine_map@100": 0.26647869540792385,
123
+ "NanoQuoraRetrieval_cosine_accuracy@1": 0.96,
124
  "NanoQuoraRetrieval_cosine_accuracy@3": 0.98,
125
  "NanoQuoraRetrieval_cosine_accuracy@5": 1.0,
126
  "NanoQuoraRetrieval_cosine_accuracy@10": 1.0,
127
+ "NanoQuoraRetrieval_cosine_precision@1": 0.96,
128
+ "NanoQuoraRetrieval_cosine_precision@3": 0.4133333333333333,
129
+ "NanoQuoraRetrieval_cosine_precision@5": 0.25999999999999995,
130
+ "NanoQuoraRetrieval_cosine_precision@10": 0.13999999999999999,
131
+ "NanoQuoraRetrieval_cosine_recall@1": 0.8373333333333332,
132
+ "NanoQuoraRetrieval_cosine_recall@3": 0.9520000000000001,
133
+ "NanoQuoraRetrieval_cosine_recall@5": 0.9793333333333334,
134
+ "NanoQuoraRetrieval_cosine_recall@10": 1.0,
135
+ "NanoQuoraRetrieval_cosine_ndcg@10": 0.9755732089084438,
136
+ "NanoQuoraRetrieval_cosine_mrr@10": 0.975,
137
+ "NanoQuoraRetrieval_cosine_map@100": 0.9623253968253969,
138
+ "NanoSCIDOCS_cosine_accuracy@1": 0.44,
139
+ "NanoSCIDOCS_cosine_accuracy@3": 0.66,
140
+ "NanoSCIDOCS_cosine_accuracy@5": 0.76,
141
+ "NanoSCIDOCS_cosine_accuracy@10": 0.82,
142
+ "NanoSCIDOCS_cosine_precision@1": 0.44,
143
+ "NanoSCIDOCS_cosine_precision@3": 0.3533333333333333,
144
+ "NanoSCIDOCS_cosine_precision@5": 0.29200000000000004,
145
+ "NanoSCIDOCS_cosine_precision@10": 0.18799999999999997,
146
+ "NanoSCIDOCS_cosine_recall@1": 0.09100000000000001,
147
+ "NanoSCIDOCS_cosine_recall@3": 0.22066666666666668,
148
+ "NanoSCIDOCS_cosine_recall@5": 0.3016666666666667,
149
+ "NanoSCIDOCS_cosine_recall@10": 0.38666666666666655,
150
+ "NanoSCIDOCS_cosine_ndcg@10": 0.3759831673953289,
151
+ "NanoSCIDOCS_cosine_mrr@10": 0.5660238095238094,
152
+ "NanoSCIDOCS_cosine_map@100": 0.2923958742502536,
153
+ "NanoArguAna_cosine_accuracy@1": 0.08,
154
  "NanoArguAna_cosine_accuracy@3": 0.18,
155
+ "NanoArguAna_cosine_accuracy@5": 0.24,
156
  "NanoArguAna_cosine_accuracy@10": 0.34,
157
+ "NanoArguAna_cosine_precision@1": 0.08,
158
  "NanoArguAna_cosine_precision@3": 0.06,
159
+ "NanoArguAna_cosine_precision@5": 0.04800000000000001,
160
  "NanoArguAna_cosine_precision@10": 0.034,
161
+ "NanoArguAna_cosine_recall@1": 0.08,
162
  "NanoArguAna_cosine_recall@3": 0.18,
163
+ "NanoArguAna_cosine_recall@5": 0.24,
164
  "NanoArguAna_cosine_recall@10": 0.34,
165
+ "NanoArguAna_cosine_ndcg@10": 0.19775950107880547,
166
+ "NanoArguAna_cosine_mrr@10": 0.1541031746031746,
167
+ "NanoArguAna_cosine_map@100": 0.1637127723917234,
168
+ "NanoSciFact_cosine_accuracy@1": 0.22,
169
+ "NanoSciFact_cosine_accuracy@3": 0.3,
170
+ "NanoSciFact_cosine_accuracy@5": 0.32,
171
+ "NanoSciFact_cosine_accuracy@10": 0.38,
172
+ "NanoSciFact_cosine_precision@1": 0.22,
173
+ "NanoSciFact_cosine_precision@3": 0.12,
174
+ "NanoSciFact_cosine_precision@5": 0.07600000000000001,
175
+ "NanoSciFact_cosine_precision@10": 0.044000000000000004,
176
+ "NanoSciFact_cosine_recall@1": 0.195,
177
+ "NanoSciFact_cosine_recall@3": 0.285,
178
+ "NanoSciFact_cosine_recall@5": 0.305,
179
+ "NanoSciFact_cosine_recall@10": 0.365,
180
+ "NanoSciFact_cosine_ndcg@10": 0.28918208458247957,
181
+ "NanoSciFact_cosine_mrr@10": 0.2718333333333333,
182
+ "NanoSciFact_cosine_map@100": 0.27817432559902106,
183
+ "NanoTouche2020_cosine_accuracy@1": 0.46938775510204084,
184
+ "NanoTouche2020_cosine_accuracy@3": 0.6530612244897959,
185
+ "NanoTouche2020_cosine_accuracy@5": 0.8163265306122449,
186
+ "NanoTouche2020_cosine_accuracy@10": 0.9591836734693877,
187
+ "NanoTouche2020_cosine_precision@1": 0.46938775510204084,
188
+ "NanoTouche2020_cosine_precision@3": 0.4081632653061224,
189
+ "NanoTouche2020_cosine_precision@5": 0.3877551020408163,
190
+ "NanoTouche2020_cosine_precision@10": 0.34285714285714286,
191
+ "NanoTouche2020_cosine_recall@1": 0.03304169886606065,
192
+ "NanoTouche2020_cosine_recall@3": 0.08663742657609082,
193
+ "NanoTouche2020_cosine_recall@5": 0.13074375193904886,
194
+ "NanoTouche2020_cosine_recall@10": 0.2206088169640079,
195
+ "NanoTouche2020_cosine_ndcg@10": 0.38115064093925494,
196
+ "NanoTouche2020_cosine_mrr@10": 0.6090055069646906,
197
+ "NanoTouche2020_cosine_map@100": 0.2635297595122428,
198
+ "NanoBEIR_mean_cosine_accuracy@1": 0.35149136577708007,
199
+ "NanoBEIR_mean_cosine_accuracy@3": 0.4902354788069073,
200
+ "NanoBEIR_mean_cosine_accuracy@5": 0.5658712715855574,
201
+ "NanoBEIR_mean_cosine_accuracy@10": 0.6491679748822605,
202
+ "NanoBEIR_mean_cosine_precision@1": 0.35149136577708007,
203
+ "NanoBEIR_mean_cosine_precision@3": 0.2257561486132915,
204
+ "NanoBEIR_mean_cosine_precision@5": 0.18121193092621668,
205
+ "NanoBEIR_mean_cosine_precision@10": 0.1285274725274725,
206
+ "NanoBEIR_mean_cosine_recall@1": 0.18446485464636025,
207
+ "NanoBEIR_mean_cosine_recall@3": 0.28725844278832385,
208
+ "NanoBEIR_mean_cosine_recall@5": 0.34314132490039767,
209
+ "NanoBEIR_mean_cosine_recall@10": 0.41258506430111763,
210
+ "NanoBEIR_mean_cosine_ndcg@10": 0.37688675285510337,
211
+ "NanoBEIR_mean_cosine_mrr@10": 0.44353216964441444,
212
+ "NanoBEIR_mean_cosine_map@100": 0.3106340488088058
213
  },
214
  "beir_touche2020": {
215
+ "BeIR-touche2020-subset-test_cosine_accuracy@1": 0.6938775510204082,
216
+ "BeIR-touche2020-subset-test_cosine_accuracy@3": 0.9183673469387755,
217
  "BeIR-touche2020-subset-test_cosine_accuracy@5": 0.9387755102040817,
218
+ "BeIR-touche2020-subset-test_cosine_accuracy@10": 1.0,
219
+ "BeIR-touche2020-subset-test_cosine_precision@1": 0.6938775510204082,
220
+ "BeIR-touche2020-subset-test_cosine_precision@3": 0.6598639455782312,
221
  "BeIR-touche2020-subset-test_cosine_precision@5": 0.6204081632653061,
222
+ "BeIR-touche2020-subset-test_cosine_precision@10": 0.5448979591836733,
223
+ "BeIR-touche2020-subset-test_cosine_recall@1": 0.015282578640721299,
224
+ "BeIR-touche2020-subset-test_cosine_recall@3": 0.043691811612696696,
225
+ "BeIR-touche2020-subset-test_cosine_recall@5": 0.06836863756086255,
226
+ "BeIR-touche2020-subset-test_cosine_recall@10": 0.12002846003612215,
227
+ "BeIR-touche2020-subset-test_cosine_ndcg@10": 0.5792925091922296,
228
+ "BeIR-touche2020-subset-test_cosine_mrr@10": 0.802437641723356,
229
+ "BeIR-touche2020-subset-test_cosine_map@100": 0.23820124526811953
230
  }
231
  }
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:83f804755eb422940037ac241ecf54da8516596e669fb776e2f9fc5297ebb299
3
- size 133462128
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b8699cdc4d5002adb5b49e94e875d00c59b4513e5607f31f33e2c8037cd8e2b5
3
+ size 596070136
special_tokens_map.json CHANGED
@@ -8,7 +8,7 @@
8
  },
9
  "mask_token": {
10
  "content": "[MASK]",
11
- "lstrip": false,
12
  "normalized": false,
13
  "rstrip": false,
14
  "single_word": false
 
8
  },
9
  "mask_token": {
10
  "content": "[MASK]",
11
+ "lstrip": true,
12
  "normalized": false,
13
  "rstrip": false,
14
  "single_word": false
tokenizer.json CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:2fc687b11de0bc1b3d8348f92e3b49ef1089a621506c7661fbf3248fcd54947e
3
- size 711649
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:218484396a9d08293b108b0e5ea31e0a1b7c801dcbed35a821deb392d2fe9bb4
3
+ size 3583485
tokenizer_config.json CHANGED
@@ -1,14 +1,230 @@
1
  {
2
  "added_tokens_decoder": {
3
  "0": {
4
- "content": "[PAD]",
 
 
 
 
 
 
 
 
5
  "lstrip": false,
6
  "normalized": false,
7
  "rstrip": false,
8
  "single_word": false,
9
  "special": true
10
  },
11
- "100": {
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
12
  "content": "[UNK]",
13
  "lstrip": false,
14
  "normalized": false,
@@ -16,7 +232,7 @@
16
  "single_word": false,
17
  "special": true
18
  },
19
- "101": {
20
  "content": "[CLS]",
21
  "lstrip": false,
22
  "normalized": false,
@@ -24,7 +240,7 @@
24
  "single_word": false,
25
  "special": true
26
  },
27
- "102": {
28
  "content": "[SEP]",
29
  "lstrip": false,
30
  "normalized": false,
@@ -32,34 +248,698 @@
32
  "single_word": false,
33
  "special": true
34
  },
35
- "103": {
36
- "content": "[MASK]",
37
  "lstrip": false,
38
  "normalized": false,
39
  "rstrip": false,
40
  "single_word": false,
41
  "special": true
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
42
  }
43
  },
44
- "clean_up_tokenization_spaces": false,
45
  "cls_token": "[CLS]",
46
- "do_basic_tokenize": true,
47
- "do_lower_case": true,
48
  "extra_special_tokens": {},
49
  "mask_token": "[MASK]",
50
- "max_length": 128,
51
- "model_max_length": 128,
52
- "never_split": null,
53
- "pad_to_multiple_of": null,
 
54
  "pad_token": "[PAD]",
55
- "pad_token_type_id": 0,
56
- "padding_side": "right",
57
  "sep_token": "[SEP]",
58
- "stride": 0,
59
- "strip_accents": null,
60
- "tokenize_chinese_chars": true,
61
- "tokenizer_class": "BertTokenizer",
62
- "truncation_side": "right",
63
- "truncation_strategy": "longest_first",
64
  "unk_token": "[UNK]"
65
  }
 
1
  {
2
  "added_tokens_decoder": {
3
  "0": {
4
+ "content": "|||IP_ADDRESS|||",
5
+ "lstrip": false,
6
+ "normalized": true,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": false
10
+ },
11
+ "1": {
12
+ "content": "<|padding|>",
13
  "lstrip": false,
14
  "normalized": false,
15
  "rstrip": false,
16
  "single_word": false,
17
  "special": true
18
  },
19
+ "50254": {
20
+ "content": " ",
21
+ "lstrip": false,
22
+ "normalized": true,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": false
26
+ },
27
+ "50255": {
28
+ "content": " ",
29
+ "lstrip": false,
30
+ "normalized": true,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": false
34
+ },
35
+ "50256": {
36
+ "content": " ",
37
+ "lstrip": false,
38
+ "normalized": true,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": false
42
+ },
43
+ "50257": {
44
+ "content": " ",
45
+ "lstrip": false,
46
+ "normalized": true,
47
+ "rstrip": false,
48
+ "single_word": false,
49
+ "special": false
50
+ },
51
+ "50258": {
52
+ "content": " ",
53
+ "lstrip": false,
54
+ "normalized": true,
55
+ "rstrip": false,
56
+ "single_word": false,
57
+ "special": false
58
+ },
59
+ "50259": {
60
+ "content": " ",
61
+ "lstrip": false,
62
+ "normalized": true,
63
+ "rstrip": false,
64
+ "single_word": false,
65
+ "special": false
66
+ },
67
+ "50260": {
68
+ "content": " ",
69
+ "lstrip": false,
70
+ "normalized": true,
71
+ "rstrip": false,
72
+ "single_word": false,
73
+ "special": false
74
+ },
75
+ "50261": {
76
+ "content": " ",
77
+ "lstrip": false,
78
+ "normalized": true,
79
+ "rstrip": false,
80
+ "single_word": false,
81
+ "special": false
82
+ },
83
+ "50262": {
84
+ "content": " ",
85
+ "lstrip": false,
86
+ "normalized": true,
87
+ "rstrip": false,
88
+ "single_word": false,
89
+ "special": false
90
+ },
91
+ "50263": {
92
+ "content": " ",
93
+ "lstrip": false,
94
+ "normalized": true,
95
+ "rstrip": false,
96
+ "single_word": false,
97
+ "special": false
98
+ },
99
+ "50264": {
100
+ "content": " ",
101
+ "lstrip": false,
102
+ "normalized": true,
103
+ "rstrip": false,
104
+ "single_word": false,
105
+ "special": false
106
+ },
107
+ "50265": {
108
+ "content": " ",
109
+ "lstrip": false,
110
+ "normalized": true,
111
+ "rstrip": false,
112
+ "single_word": false,
113
+ "special": false
114
+ },
115
+ "50266": {
116
+ "content": " ",
117
+ "lstrip": false,
118
+ "normalized": true,
119
+ "rstrip": false,
120
+ "single_word": false,
121
+ "special": false
122
+ },
123
+ "50267": {
124
+ "content": " ",
125
+ "lstrip": false,
126
+ "normalized": true,
127
+ "rstrip": false,
128
+ "single_word": false,
129
+ "special": false
130
+ },
131
+ "50268": {
132
+ "content": " ",
133
+ "lstrip": false,
134
+ "normalized": true,
135
+ "rstrip": false,
136
+ "single_word": false,
137
+ "special": false
138
+ },
139
+ "50269": {
140
+ "content": " ",
141
+ "lstrip": false,
142
+ "normalized": true,
143
+ "rstrip": false,
144
+ "single_word": false,
145
+ "special": false
146
+ },
147
+ "50270": {
148
+ "content": " ",
149
+ "lstrip": false,
150
+ "normalized": true,
151
+ "rstrip": false,
152
+ "single_word": false,
153
+ "special": false
154
+ },
155
+ "50271": {
156
+ "content": " ",
157
+ "lstrip": false,
158
+ "normalized": true,
159
+ "rstrip": false,
160
+ "single_word": false,
161
+ "special": false
162
+ },
163
+ "50272": {
164
+ "content": " ",
165
+ "lstrip": false,
166
+ "normalized": true,
167
+ "rstrip": false,
168
+ "single_word": false,
169
+ "special": false
170
+ },
171
+ "50273": {
172
+ "content": " ",
173
+ "lstrip": false,
174
+ "normalized": true,
175
+ "rstrip": false,
176
+ "single_word": false,
177
+ "special": false
178
+ },
179
+ "50274": {
180
+ "content": " ",
181
+ "lstrip": false,
182
+ "normalized": true,
183
+ "rstrip": false,
184
+ "single_word": false,
185
+ "special": false
186
+ },
187
+ "50275": {
188
+ "content": " ",
189
+ "lstrip": false,
190
+ "normalized": true,
191
+ "rstrip": false,
192
+ "single_word": false,
193
+ "special": false
194
+ },
195
+ "50276": {
196
+ "content": " ",
197
+ "lstrip": false,
198
+ "normalized": true,
199
+ "rstrip": false,
200
+ "single_word": false,
201
+ "special": false
202
+ },
203
+ "50277": {
204
+ "content": "|||EMAIL_ADDRESS|||",
205
+ "lstrip": false,
206
+ "normalized": true,
207
+ "rstrip": false,
208
+ "single_word": false,
209
+ "special": false
210
+ },
211
+ "50278": {
212
+ "content": "|||PHONE_NUMBER|||",
213
+ "lstrip": false,
214
+ "normalized": true,
215
+ "rstrip": false,
216
+ "single_word": false,
217
+ "special": false
218
+ },
219
+ "50279": {
220
+ "content": "<|endoftext|>",
221
+ "lstrip": false,
222
+ "normalized": false,
223
+ "rstrip": false,
224
+ "single_word": false,
225
+ "special": true
226
+ },
227
+ "50280": {
228
  "content": "[UNK]",
229
  "lstrip": false,
230
  "normalized": false,
 
232
  "single_word": false,
233
  "special": true
234
  },
235
+ "50281": {
236
  "content": "[CLS]",
237
  "lstrip": false,
238
  "normalized": false,
 
240
  "single_word": false,
241
  "special": true
242
  },
243
+ "50282": {
244
  "content": "[SEP]",
245
  "lstrip": false,
246
  "normalized": false,
 
248
  "single_word": false,
249
  "special": true
250
  },
251
+ "50283": {
252
+ "content": "[PAD]",
253
  "lstrip": false,
254
  "normalized": false,
255
  "rstrip": false,
256
  "single_word": false,
257
  "special": true
258
+ },
259
+ "50284": {
260
+ "content": "[MASK]",
261
+ "lstrip": true,
262
+ "normalized": false,
263
+ "rstrip": false,
264
+ "single_word": false,
265
+ "special": true
266
+ },
267
+ "50285": {
268
+ "content": "[unused0]",
269
+ "lstrip": false,
270
+ "normalized": true,
271
+ "rstrip": false,
272
+ "single_word": false,
273
+ "special": false
274
+ },
275
+ "50286": {
276
+ "content": "[unused1]",
277
+ "lstrip": false,
278
+ "normalized": true,
279
+ "rstrip": false,
280
+ "single_word": false,
281
+ "special": false
282
+ },
283
+ "50287": {
284
+ "content": "[unused2]",
285
+ "lstrip": false,
286
+ "normalized": true,
287
+ "rstrip": false,
288
+ "single_word": false,
289
+ "special": false
290
+ },
291
+ "50288": {
292
+ "content": "[unused3]",
293
+ "lstrip": false,
294
+ "normalized": true,
295
+ "rstrip": false,
296
+ "single_word": false,
297
+ "special": false
298
+ },
299
+ "50289": {
300
+ "content": "[unused4]",
301
+ "lstrip": false,
302
+ "normalized": true,
303
+ "rstrip": false,
304
+ "single_word": false,
305
+ "special": false
306
+ },
307
+ "50290": {
308
+ "content": "[unused5]",
309
+ "lstrip": false,
310
+ "normalized": true,
311
+ "rstrip": false,
312
+ "single_word": false,
313
+ "special": false
314
+ },
315
+ "50291": {
316
+ "content": "[unused6]",
317
+ "lstrip": false,
318
+ "normalized": true,
319
+ "rstrip": false,
320
+ "single_word": false,
321
+ "special": false
322
+ },
323
+ "50292": {
324
+ "content": "[unused7]",
325
+ "lstrip": false,
326
+ "normalized": true,
327
+ "rstrip": false,
328
+ "single_word": false,
329
+ "special": false
330
+ },
331
+ "50293": {
332
+ "content": "[unused8]",
333
+ "lstrip": false,
334
+ "normalized": true,
335
+ "rstrip": false,
336
+ "single_word": false,
337
+ "special": false
338
+ },
339
+ "50294": {
340
+ "content": "[unused9]",
341
+ "lstrip": false,
342
+ "normalized": true,
343
+ "rstrip": false,
344
+ "single_word": false,
345
+ "special": false
346
+ },
347
+ "50295": {
348
+ "content": "[unused10]",
349
+ "lstrip": false,
350
+ "normalized": true,
351
+ "rstrip": false,
352
+ "single_word": false,
353
+ "special": false
354
+ },
355
+ "50296": {
356
+ "content": "[unused11]",
357
+ "lstrip": false,
358
+ "normalized": true,
359
+ "rstrip": false,
360
+ "single_word": false,
361
+ "special": false
362
+ },
363
+ "50297": {
364
+ "content": "[unused12]",
365
+ "lstrip": false,
366
+ "normalized": true,
367
+ "rstrip": false,
368
+ "single_word": false,
369
+ "special": false
370
+ },
371
+ "50298": {
372
+ "content": "[unused13]",
373
+ "lstrip": false,
374
+ "normalized": true,
375
+ "rstrip": false,
376
+ "single_word": false,
377
+ "special": false
378
+ },
379
+ "50299": {
380
+ "content": "[unused14]",
381
+ "lstrip": false,
382
+ "normalized": true,
383
+ "rstrip": false,
384
+ "single_word": false,
385
+ "special": false
386
+ },
387
+ "50300": {
388
+ "content": "[unused15]",
389
+ "lstrip": false,
390
+ "normalized": true,
391
+ "rstrip": false,
392
+ "single_word": false,
393
+ "special": false
394
+ },
395
+ "50301": {
396
+ "content": "[unused16]",
397
+ "lstrip": false,
398
+ "normalized": true,
399
+ "rstrip": false,
400
+ "single_word": false,
401
+ "special": false
402
+ },
403
+ "50302": {
404
+ "content": "[unused17]",
405
+ "lstrip": false,
406
+ "normalized": true,
407
+ "rstrip": false,
408
+ "single_word": false,
409
+ "special": false
410
+ },
411
+ "50303": {
412
+ "content": "[unused18]",
413
+ "lstrip": false,
414
+ "normalized": true,
415
+ "rstrip": false,
416
+ "single_word": false,
417
+ "special": false
418
+ },
419
+ "50304": {
420
+ "content": "[unused19]",
421
+ "lstrip": false,
422
+ "normalized": true,
423
+ "rstrip": false,
424
+ "single_word": false,
425
+ "special": false
426
+ },
427
+ "50305": {
428
+ "content": "[unused20]",
429
+ "lstrip": false,
430
+ "normalized": true,
431
+ "rstrip": false,
432
+ "single_word": false,
433
+ "special": false
434
+ },
435
+ "50306": {
436
+ "content": "[unused21]",
437
+ "lstrip": false,
438
+ "normalized": true,
439
+ "rstrip": false,
440
+ "single_word": false,
441
+ "special": false
442
+ },
443
+ "50307": {
444
+ "content": "[unused22]",
445
+ "lstrip": false,
446
+ "normalized": true,
447
+ "rstrip": false,
448
+ "single_word": false,
449
+ "special": false
450
+ },
451
+ "50308": {
452
+ "content": "[unused23]",
453
+ "lstrip": false,
454
+ "normalized": true,
455
+ "rstrip": false,
456
+ "single_word": false,
457
+ "special": false
458
+ },
459
+ "50309": {
460
+ "content": "[unused24]",
461
+ "lstrip": false,
462
+ "normalized": true,
463
+ "rstrip": false,
464
+ "single_word": false,
465
+ "special": false
466
+ },
467
+ "50310": {
468
+ "content": "[unused25]",
469
+ "lstrip": false,
470
+ "normalized": true,
471
+ "rstrip": false,
472
+ "single_word": false,
473
+ "special": false
474
+ },
475
+ "50311": {
476
+ "content": "[unused26]",
477
+ "lstrip": false,
478
+ "normalized": true,
479
+ "rstrip": false,
480
+ "single_word": false,
481
+ "special": false
482
+ },
483
+ "50312": {
484
+ "content": "[unused27]",
485
+ "lstrip": false,
486
+ "normalized": true,
487
+ "rstrip": false,
488
+ "single_word": false,
489
+ "special": false
490
+ },
491
+ "50313": {
492
+ "content": "[unused28]",
493
+ "lstrip": false,
494
+ "normalized": true,
495
+ "rstrip": false,
496
+ "single_word": false,
497
+ "special": false
498
+ },
499
+ "50314": {
500
+ "content": "[unused29]",
501
+ "lstrip": false,
502
+ "normalized": true,
503
+ "rstrip": false,
504
+ "single_word": false,
505
+ "special": false
506
+ },
507
+ "50315": {
508
+ "content": "[unused30]",
509
+ "lstrip": false,
510
+ "normalized": true,
511
+ "rstrip": false,
512
+ "single_word": false,
513
+ "special": false
514
+ },
515
+ "50316": {
516
+ "content": "[unused31]",
517
+ "lstrip": false,
518
+ "normalized": true,
519
+ "rstrip": false,
520
+ "single_word": false,
521
+ "special": false
522
+ },
523
+ "50317": {
524
+ "content": "[unused32]",
525
+ "lstrip": false,
526
+ "normalized": true,
527
+ "rstrip": false,
528
+ "single_word": false,
529
+ "special": false
530
+ },
531
+ "50318": {
532
+ "content": "[unused33]",
533
+ "lstrip": false,
534
+ "normalized": true,
535
+ "rstrip": false,
536
+ "single_word": false,
537
+ "special": false
538
+ },
539
+ "50319": {
540
+ "content": "[unused34]",
541
+ "lstrip": false,
542
+ "normalized": true,
543
+ "rstrip": false,
544
+ "single_word": false,
545
+ "special": false
546
+ },
547
+ "50320": {
548
+ "content": "[unused35]",
549
+ "lstrip": false,
550
+ "normalized": true,
551
+ "rstrip": false,
552
+ "single_word": false,
553
+ "special": false
554
+ },
555
+ "50321": {
556
+ "content": "[unused36]",
557
+ "lstrip": false,
558
+ "normalized": true,
559
+ "rstrip": false,
560
+ "single_word": false,
561
+ "special": false
562
+ },
563
+ "50322": {
564
+ "content": "[unused37]",
565
+ "lstrip": false,
566
+ "normalized": true,
567
+ "rstrip": false,
568
+ "single_word": false,
569
+ "special": false
570
+ },
571
+ "50323": {
572
+ "content": "[unused38]",
573
+ "lstrip": false,
574
+ "normalized": true,
575
+ "rstrip": false,
576
+ "single_word": false,
577
+ "special": false
578
+ },
579
+ "50324": {
580
+ "content": "[unused39]",
581
+ "lstrip": false,
582
+ "normalized": true,
583
+ "rstrip": false,
584
+ "single_word": false,
585
+ "special": false
586
+ },
587
+ "50325": {
588
+ "content": "[unused40]",
589
+ "lstrip": false,
590
+ "normalized": true,
591
+ "rstrip": false,
592
+ "single_word": false,
593
+ "special": false
594
+ },
595
+ "50326": {
596
+ "content": "[unused41]",
597
+ "lstrip": false,
598
+ "normalized": true,
599
+ "rstrip": false,
600
+ "single_word": false,
601
+ "special": false
602
+ },
603
+ "50327": {
604
+ "content": "[unused42]",
605
+ "lstrip": false,
606
+ "normalized": true,
607
+ "rstrip": false,
608
+ "single_word": false,
609
+ "special": false
610
+ },
611
+ "50328": {
612
+ "content": "[unused43]",
613
+ "lstrip": false,
614
+ "normalized": true,
615
+ "rstrip": false,
616
+ "single_word": false,
617
+ "special": false
618
+ },
619
+ "50329": {
620
+ "content": "[unused44]",
621
+ "lstrip": false,
622
+ "normalized": true,
623
+ "rstrip": false,
624
+ "single_word": false,
625
+ "special": false
626
+ },
627
+ "50330": {
628
+ "content": "[unused45]",
629
+ "lstrip": false,
630
+ "normalized": true,
631
+ "rstrip": false,
632
+ "single_word": false,
633
+ "special": false
634
+ },
635
+ "50331": {
636
+ "content": "[unused46]",
637
+ "lstrip": false,
638
+ "normalized": true,
639
+ "rstrip": false,
640
+ "single_word": false,
641
+ "special": false
642
+ },
643
+ "50332": {
644
+ "content": "[unused47]",
645
+ "lstrip": false,
646
+ "normalized": true,
647
+ "rstrip": false,
648
+ "single_word": false,
649
+ "special": false
650
+ },
651
+ "50333": {
652
+ "content": "[unused48]",
653
+ "lstrip": false,
654
+ "normalized": true,
655
+ "rstrip": false,
656
+ "single_word": false,
657
+ "special": false
658
+ },
659
+ "50334": {
660
+ "content": "[unused49]",
661
+ "lstrip": false,
662
+ "normalized": true,
663
+ "rstrip": false,
664
+ "single_word": false,
665
+ "special": false
666
+ },
667
+ "50335": {
668
+ "content": "[unused50]",
669
+ "lstrip": false,
670
+ "normalized": true,
671
+ "rstrip": false,
672
+ "single_word": false,
673
+ "special": false
674
+ },
675
+ "50336": {
676
+ "content": "[unused51]",
677
+ "lstrip": false,
678
+ "normalized": true,
679
+ "rstrip": false,
680
+ "single_word": false,
681
+ "special": false
682
+ },
683
+ "50337": {
684
+ "content": "[unused52]",
685
+ "lstrip": false,
686
+ "normalized": true,
687
+ "rstrip": false,
688
+ "single_word": false,
689
+ "special": false
690
+ },
691
+ "50338": {
692
+ "content": "[unused53]",
693
+ "lstrip": false,
694
+ "normalized": true,
695
+ "rstrip": false,
696
+ "single_word": false,
697
+ "special": false
698
+ },
699
+ "50339": {
700
+ "content": "[unused54]",
701
+ "lstrip": false,
702
+ "normalized": true,
703
+ "rstrip": false,
704
+ "single_word": false,
705
+ "special": false
706
+ },
707
+ "50340": {
708
+ "content": "[unused55]",
709
+ "lstrip": false,
710
+ "normalized": true,
711
+ "rstrip": false,
712
+ "single_word": false,
713
+ "special": false
714
+ },
715
+ "50341": {
716
+ "content": "[unused56]",
717
+ "lstrip": false,
718
+ "normalized": true,
719
+ "rstrip": false,
720
+ "single_word": false,
721
+ "special": false
722
+ },
723
+ "50342": {
724
+ "content": "[unused57]",
725
+ "lstrip": false,
726
+ "normalized": true,
727
+ "rstrip": false,
728
+ "single_word": false,
729
+ "special": false
730
+ },
731
+ "50343": {
732
+ "content": "[unused58]",
733
+ "lstrip": false,
734
+ "normalized": true,
735
+ "rstrip": false,
736
+ "single_word": false,
737
+ "special": false
738
+ },
739
+ "50344": {
740
+ "content": "[unused59]",
741
+ "lstrip": false,
742
+ "normalized": true,
743
+ "rstrip": false,
744
+ "single_word": false,
745
+ "special": false
746
+ },
747
+ "50345": {
748
+ "content": "[unused60]",
749
+ "lstrip": false,
750
+ "normalized": true,
751
+ "rstrip": false,
752
+ "single_word": false,
753
+ "special": false
754
+ },
755
+ "50346": {
756
+ "content": "[unused61]",
757
+ "lstrip": false,
758
+ "normalized": true,
759
+ "rstrip": false,
760
+ "single_word": false,
761
+ "special": false
762
+ },
763
+ "50347": {
764
+ "content": "[unused62]",
765
+ "lstrip": false,
766
+ "normalized": true,
767
+ "rstrip": false,
768
+ "single_word": false,
769
+ "special": false
770
+ },
771
+ "50348": {
772
+ "content": "[unused63]",
773
+ "lstrip": false,
774
+ "normalized": true,
775
+ "rstrip": false,
776
+ "single_word": false,
777
+ "special": false
778
+ },
779
+ "50349": {
780
+ "content": "[unused64]",
781
+ "lstrip": false,
782
+ "normalized": true,
783
+ "rstrip": false,
784
+ "single_word": false,
785
+ "special": false
786
+ },
787
+ "50350": {
788
+ "content": "[unused65]",
789
+ "lstrip": false,
790
+ "normalized": true,
791
+ "rstrip": false,
792
+ "single_word": false,
793
+ "special": false
794
+ },
795
+ "50351": {
796
+ "content": "[unused66]",
797
+ "lstrip": false,
798
+ "normalized": true,
799
+ "rstrip": false,
800
+ "single_word": false,
801
+ "special": false
802
+ },
803
+ "50352": {
804
+ "content": "[unused67]",
805
+ "lstrip": false,
806
+ "normalized": true,
807
+ "rstrip": false,
808
+ "single_word": false,
809
+ "special": false
810
+ },
811
+ "50353": {
812
+ "content": "[unused68]",
813
+ "lstrip": false,
814
+ "normalized": true,
815
+ "rstrip": false,
816
+ "single_word": false,
817
+ "special": false
818
+ },
819
+ "50354": {
820
+ "content": "[unused69]",
821
+ "lstrip": false,
822
+ "normalized": true,
823
+ "rstrip": false,
824
+ "single_word": false,
825
+ "special": false
826
+ },
827
+ "50355": {
828
+ "content": "[unused70]",
829
+ "lstrip": false,
830
+ "normalized": true,
831
+ "rstrip": false,
832
+ "single_word": false,
833
+ "special": false
834
+ },
835
+ "50356": {
836
+ "content": "[unused71]",
837
+ "lstrip": false,
838
+ "normalized": true,
839
+ "rstrip": false,
840
+ "single_word": false,
841
+ "special": false
842
+ },
843
+ "50357": {
844
+ "content": "[unused72]",
845
+ "lstrip": false,
846
+ "normalized": true,
847
+ "rstrip": false,
848
+ "single_word": false,
849
+ "special": false
850
+ },
851
+ "50358": {
852
+ "content": "[unused73]",
853
+ "lstrip": false,
854
+ "normalized": true,
855
+ "rstrip": false,
856
+ "single_word": false,
857
+ "special": false
858
+ },
859
+ "50359": {
860
+ "content": "[unused74]",
861
+ "lstrip": false,
862
+ "normalized": true,
863
+ "rstrip": false,
864
+ "single_word": false,
865
+ "special": false
866
+ },
867
+ "50360": {
868
+ "content": "[unused75]",
869
+ "lstrip": false,
870
+ "normalized": true,
871
+ "rstrip": false,
872
+ "single_word": false,
873
+ "special": false
874
+ },
875
+ "50361": {
876
+ "content": "[unused76]",
877
+ "lstrip": false,
878
+ "normalized": true,
879
+ "rstrip": false,
880
+ "single_word": false,
881
+ "special": false
882
+ },
883
+ "50362": {
884
+ "content": "[unused77]",
885
+ "lstrip": false,
886
+ "normalized": true,
887
+ "rstrip": false,
888
+ "single_word": false,
889
+ "special": false
890
+ },
891
+ "50363": {
892
+ "content": "[unused78]",
893
+ "lstrip": false,
894
+ "normalized": true,
895
+ "rstrip": false,
896
+ "single_word": false,
897
+ "special": false
898
+ },
899
+ "50364": {
900
+ "content": "[unused79]",
901
+ "lstrip": false,
902
+ "normalized": true,
903
+ "rstrip": false,
904
+ "single_word": false,
905
+ "special": false
906
+ },
907
+ "50365": {
908
+ "content": "[unused80]",
909
+ "lstrip": false,
910
+ "normalized": true,
911
+ "rstrip": false,
912
+ "single_word": false,
913
+ "special": false
914
+ },
915
+ "50366": {
916
+ "content": "[unused81]",
917
+ "lstrip": false,
918
+ "normalized": true,
919
+ "rstrip": false,
920
+ "single_word": false,
921
+ "special": false
922
+ },
923
+ "50367": {
924
+ "content": "[unused82]",
925
+ "lstrip": false,
926
+ "normalized": true,
927
+ "rstrip": false,
928
+ "single_word": false,
929
+ "special": false
930
  }
931
  },
932
+ "clean_up_tokenization_spaces": true,
933
  "cls_token": "[CLS]",
 
 
934
  "extra_special_tokens": {},
935
  "mask_token": "[MASK]",
936
+ "model_input_names": [
937
+ "input_ids",
938
+ "attention_mask"
939
+ ],
940
+ "model_max_length": 1000000000000000019884624838656,
941
  "pad_token": "[PAD]",
 
 
942
  "sep_token": "[SEP]",
943
+ "tokenizer_class": "PreTrainedTokenizerFast",
 
 
 
 
 
944
  "unk_token": "[UNK]"
945
  }