Training in progress, step 1687

Information-Retrieval_evaluation_BeIR-touche2020-subset-test_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.7142857142857143,0.9591836734693877,1.0,1.0,0.7142857142857143,0.015880404635022063,0.7006802721088435,0.04648085765992207,0.689795918367347,0.07606536341929133,0.6306122448979592,0.13922476411011186,0.8435374149659863,0.6529991617140374,0.2850802517047579
 -1,-1,0.6938775510204082,0.9591836734693877,1.0,1.0,0.6938775510204082,0.015318508143902818,0.7414965986394558,0.049323085700107676,0.7387755102040818,0.08177075427838504,0.6469387755102041,0.1429596074128849,0.8333333333333334,0.6732632834630611,0.3042931320883796
 -1,-1,0.7755102040816326,0.9795918367346939,1.0,1.0,0.7755102040816326,0.017161759287106504,0.7551020408163265,0.050083191794989906,0.7265306122448978,0.08004301263609473,0.6571428571428573,0.14521580076391974,0.8714285714285713,0.6892612517303571,0.3065539748752648
+-1,-1,0.6938775510204082,0.9591836734693877,0.9591836734693877,1.0,0.6938775510204082,0.01524437495344929,0.7142857142857142,0.047106170818450595,0.6489795918367348,0.07152292375348247,0.5693877551020408,0.125504336824092,0.8226433430515063,0.6061049268897444,0.2612230144327072

Information-Retrieval_evaluation_NanoArguAna_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.18,0.42,0.56,0.72,0.18,0.18,0.13999999999999999,0.42,0.11200000000000002,0.56,0.07200000000000001,0.72,0.3527380952380952,0.4408093391709953,0.36502285132354245
 -1,-1,0.24,0.56,0.72,0.9,0.24,0.24,0.18666666666666668,0.56,0.14400000000000002,0.72,0.08999999999999998,0.9,0.4394126984126983,0.5492042488144615,0.44569247841530457
 -1,-1,0.2,0.44,0.66,0.82,0.2,0.2,0.14666666666666664,0.44,0.132,0.66,0.08199999999999999,0.82,0.3852460317460317,0.4889503790004362,0.3927867585630743
+-1,-1,0.2,0.4,0.58,0.76,0.2,0.2,0.13333333333333333,0.4,0.11600000000000002,0.58,0.07600000000000001,0.76,0.3499444444444444,0.445906963986827,0.3549188614872763

Information-Retrieval_evaluation_NanoClimateFEVER_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.22,0.44,0.52,0.62,0.22,0.10166666666666666,0.14666666666666664,0.22166666666666665,0.12000000000000002,0.2723333333333333,0.07800000000000001,0.33899999999999997,0.34035714285714286,0.26147069275043155,0.1981781964878655
 -1,-1,0.28,0.5,0.58,0.68,0.28,0.11833333333333335,0.1733333333333333,0.22833333333333333,0.12,0.2633333333333333,0.078,0.34,0.40621428571428564,0.2808903614305741,0.22360631242088647
 -1,-1,0.28,0.5,0.64,0.7,0.28,0.12333333333333332,0.18666666666666665,0.24333333333333332,0.14800000000000002,0.31566666666666665,0.08199999999999999,0.3423333333333333,0.41155555555555556,0.2907447124874634,0.22664092730177512
+-1,-1,0.26,0.36,0.44,0.52,0.26,0.14166666666666666,0.12,0.19,0.092,0.22333333333333336,0.062,0.2723333333333333,0.33557936507936503,0.2436767141441193,0.20217806834795687

Information-Retrieval_evaluation_NanoDBPedia_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.76,0.86,0.86,0.94,0.76,0.08063316412620315,0.5266666666666666,0.14548790439401796,0.44400000000000006,0.18155499933794458,0.36800000000000005,0.25981708633550893,0.8098571428571429,0.49239230047602567,0.32859171288950245
 -1,-1,0.72,0.86,0.9,0.94,0.72,0.059622019903194524,0.54,0.14445602791486953,0.468,0.1935947024951166,0.3940000000000001,0.2762600742290385,0.7943333333333333,0.504599041585888,0.32904250829639836
 -1,-1,0.72,0.88,0.88,0.94,0.72,0.0837828590640337,0.5533333333333333,0.16110714540075896,0.4600000000000001,0.19518511267382124,0.386,0.2697616826690356,0.7983333333333335,0.5084374485621219,0.3354481672493977
+-1,-1,0.56,0.8,0.86,0.9,0.56,0.057167885222086164,0.5,0.12515612374824867,0.44,0.1822183603452181,0.35,0.24167414201200188,0.6821904761904762,0.4445153910998771,0.276586633736675

Information-Retrieval_evaluation_NanoFEVER_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.58,0.86,0.96,0.98,0.58,0.5366666666666666,0.29333333333333333,0.8066666666666668,0.19599999999999995,0.9066666666666667,0.09999999999999998,0.9266666666666667,0.7339999999999999,0.7606626704790038,0.6934942151344591
 -1,-1,0.86,0.94,0.98,0.98,0.86,0.7966666666666665,0.3133333333333333,0.8766666666666666,0.19999999999999996,0.9266666666666667,0.102,0.9366666666666668,0.9066666666666667,0.8843956236619556,0.8506153234682645
 -1,-1,0.78,0.98,0.98,0.98,0.78,0.7366666666666666,0.32666666666666666,0.9166666666666667,0.19999999999999996,0.9266666666666667,0.09999999999999998,0.9266666666666667,0.8633333333333332,0.8547856660415037,0.8163245045176333
+-1,-1,0.62,0.8,0.86,0.9,0.62,0.5866666666666667,0.2733333333333333,0.7533333333333333,0.18,0.8133333333333332,0.09399999999999999,0.8533333333333333,0.7168571428571429,0.7336687791965945,0.687890775890776

Information-Retrieval_evaluation_NanoFiQA2018_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.34,0.48,0.58,0.68,0.34,0.19707936507936508,0.19333333333333333,0.28743650793650793,0.15200000000000002,0.37743650793650796,0.102,0.46865873015873016,0.432579365079365,0.3701303439254182,0.30658113651019275
 -1,-1,0.38,0.6,0.66,0.7,0.38,0.19941269841269843,0.25333333333333335,0.38082539682539684,0.19599999999999998,0.46984920634920635,0.10799999999999998,0.5010714285714285,0.4950238095238095,0.41915583106695115,0.35716185205965095
 -1,-1,0.32,0.46,0.6,0.68,0.32,0.1880793650793651,0.19333333333333333,0.2747698412698413,0.16,0.3924365079365079,0.09599999999999997,0.46096031746031746,0.4274920634920635,0.3645000219538997,0.29800480481282754
+-1,-1,0.34,0.48,0.54,0.68,0.34,0.17952380952380953,0.18,0.27874603174603174,0.14,0.33376984126984127,0.09599999999999997,0.4741587301587301,0.43,0.3576193898882579,0.28259055809600414

Information-Retrieval_evaluation_NanoHotpotQA_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.66,0.76,0.82,0.86,0.66,0.33,0.3133333333333333,0.47,0.204,0.51,0.11599999999999998,0.58,0.7235238095238097,0.5558933426692172,0.48029489574224554
 -1,-1,0.84,0.86,0.92,0.94,0.84,0.42,0.3933333333333333,0.59,0.25999999999999995,0.65,0.13999999999999999,0.7,0.8662222222222223,0.6904287289107535,0.6155516771430958
 -1,-1,0.74,0.84,0.86,0.88,0.74,0.37,0.38666666666666666,0.58,0.248,0.62,0.12999999999999998,0.65,0.7873333333333333,0.6362626999276922,0.5727077888418632
+-1,-1,0.48,0.64,0.72,0.78,0.48,0.24,0.24666666666666665,0.37,0.17199999999999996,0.43,0.09799999999999999,0.49,0.5775238095238096,0.4426260898247735,0.36293313513648634

Information-Retrieval_evaluation_NanoMSMARCO_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.32,0.52,0.62,0.72,0.32,0.32,0.1733333333333333,0.52,0.124,0.62,0.07200000000000001,0.72,0.45404761904761903,0.5182449787606596,0.4681213273999474
 -1,-1,0.46,0.64,0.76,0.84,0.46,0.46,0.21333333333333332,0.64,0.15200000000000002,0.76,0.08399999999999999,0.84,0.5786904761904762,0.6415212118347274,0.586056624889745
 -1,-1,0.32,0.56,0.66,0.76,0.32,0.32,0.18666666666666668,0.56,0.132,0.66,0.07600000000000001,0.76,0.474047619047619,0.543482168903518,0.48355956186670473
+-1,-1,0.3,0.58,0.6,0.7,0.3,0.3,0.19333333333333333,0.58,0.12,0.6,0.07,0.7,0.44874603174603167,0.5101349275378135,0.4606212065533731

Information-Retrieval_evaluation_NanoNFCorpus_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.38,0.46,0.52,0.66,0.38,0.013257687088254642,0.3133333333333333,0.053362266003216766,0.3,0.07093283015038292,0.25,0.10042628570164332,0.4445238095238095,0.2817431194318882,0.10929807860221158
 -1,-1,0.36,0.44,0.5,0.7,0.36,0.013403039631924156,0.30666666666666664,0.034108347723976064,0.31200000000000006,0.05787770095682255,0.282,0.10590322051450729,0.43876984126984125,0.3022203221255576,0.12407610278799032
 -1,-1,0.36,0.5,0.56,0.68,0.36,0.011117260803746984,0.3533333333333333,0.06793780077947238,0.32,0.08600906529821184,0.284,0.12489478806450519,0.4486904761904762,0.31419371833661064,0.1305557027672931
+-1,-1,0.36,0.42,0.58,0.62,0.36,0.011413047310317982,0.2866666666666666,0.02700258816152921,0.304,0.04979610755705784,0.242,0.07563880594353418,0.43044444444444446,0.2645713317352105,0.08670541591415526

Information-Retrieval_evaluation_NanoNQ_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.38,0.52,0.58,0.68,0.38,0.36,0.18666666666666665,0.5,0.128,0.57,0.07400000000000001,0.65,0.4693888888888889,0.5077165748328921,0.4690841393696577
 -1,-1,0.42,0.56,0.62,0.74,0.42,0.39,0.19333333333333333,0.53,0.128,0.59,0.07800000000000001,0.7,0.5129047619047619,0.5454496947645364,0.5024388849786283
 -1,-1,0.42,0.56,0.6,0.76,0.42,0.39,0.2,0.55,0.132,0.59,0.08199999999999999,0.74,0.5029365079365079,0.5531504219817556,0.5003951480571269
+-1,-1,0.28,0.48,0.52,0.58,0.28,0.26,0.16,0.44,0.11200000000000002,0.5,0.06400000000000002,0.57,0.3893888888888889,0.42522283720602283,0.38784914899138384

Information-Retrieval_evaluation_NanoQuoraRetrieval_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.84,0.94,0.94,0.98,0.84,0.7173333333333332,0.3933333333333333,0.9053333333333333,0.244,0.9159999999999999,0.13,0.9666666666666666,0.8933333333333333,0.9006242971403466,0.8752974569290359
 -1,-1,0.88,0.98,0.98,0.98,0.88,0.7573333333333332,0.4133333333333333,0.9520000000000001,0.25599999999999995,0.9626666666666667,0.13399999999999998,0.9733333333333334,0.9266666666666665,0.9270486783685107,0.9045211951447246
 -1,-1,0.82,0.94,0.94,0.96,0.82,0.7073333333333331,0.3933333333333333,0.9053333333333333,0.24799999999999997,0.9226666666666666,0.12999999999999998,0.95,0.8761904761904762,0.8855845442596749,0.8602467532467531
+-1,-1,0.8,0.94,0.94,0.96,0.8,0.6873333333333334,0.3999999999999999,0.9086666666666667,0.24799999999999997,0.922,0.12999999999999998,0.95,0.8691666666666668,0.8827689846162723,0.8574092460390633

Information-Retrieval_evaluation_NanoSCIDOCS_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.4,0.7,0.74,0.84,0.4,0.08466666666666668,0.36,0.22266666666666665,0.28800000000000003,0.2946666666666667,0.19399999999999998,0.39866666666666667,0.5551666666666666,0.3809616035398974,0.3008044801385356
 -1,-1,0.34,0.6,0.64,0.7,0.34,0.068,0.29333333333333333,0.18066666666666664,0.256,0.26166666666666666,0.16,0.32666666666666666,0.4745,0.3163887471562768,0.25352706065216835
 -1,-1,0.5,0.7,0.84,0.9,0.5,0.10466666666666667,0.38,0.23366666666666666,0.324,0.33166666666666667,0.20199999999999999,0.4126666666666667,0.6263571428571427,0.4094545669474307,0.3236610548684944
+-1,-1,0.5,0.68,0.74,0.8,0.5,0.10200000000000001,0.3399999999999999,0.2096666666666666,0.25599999999999995,0.2626666666666666,0.16799999999999998,0.3436666666666666,0.602079365079365,0.3562789819319996,0.27946780160236867

Information-Retrieval_evaluation_NanoSciFact_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.42,0.52,0.58,0.76,0.42,0.385,0.19333333333333336,0.495,0.132,0.56,0.08799999999999997,0.76,0.5094523809523809,0.5619609261041664,0.5017938571426928
 -1,-1,0.56,0.7,0.76,0.86,0.56,0.525,0.26,0.685,0.17599999999999993,0.76,0.09799999999999999,0.86,0.6533333333333334,0.7001825387103408,0.6537051282051283
 -1,-1,0.52,0.68,0.76,0.84,0.52,0.485,0.2533333333333333,0.675,0.16799999999999998,0.745,0.09599999999999997,0.84,0.6191666666666666,0.671924698303424,0.62085644979463
+-1,-1,0.34,0.5,0.54,0.64,0.34,0.305,0.18,0.47,0.12400000000000003,0.52,0.07400000000000001,0.63,0.42055555555555557,0.4615164989979999,0.41540588317922533

Information-Retrieval_evaluation_NanoTouche2020_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.5510204081632653,0.8163265306122449,0.8979591836734694,0.9591836734693877,0.5510204081632653,0.041044891235058834,0.5170068027210885,0.10963776356983411,0.5142857142857142,0.18394414517370525,0.4061224489795918,0.27014866763261464,0.6948979591836734,0.459508446851825,0.3482148481211664
 -1,-1,0.6122448979591837,0.8163265306122449,0.8571428571428571,0.9795918367346939,0.6122448979591837,0.04304363166329577,0.510204081632653,0.11188673681342907,0.4857142857142857,0.1733248139294994,0.4061224489795919,0.2762963017123755,0.7385163589245223,0.4663612119909862,0.3560529751052228
 -1,-1,0.6122448979591837,0.7959183673469388,0.8367346938775511,0.9387755102040817,0.6122448979591837,0.0433302805209062,0.5510204081632653,0.11568403812254441,0.4857142857142857,0.1720207249983863,0.3979591836734694,0.2723164824635157,0.719355361192096,0.4631689306459952,0.3565905399507358
+-1,-1,0.5102040816326531,0.8163265306122449,0.8367346938775511,0.9387755102040817,0.5102040816326531,0.035653320582606944,0.510204081632653,0.11069986483333172,0.4530612244897959,0.16287568558624005,0.37755102040816324,0.25329274421765885,0.6645124716553287,0.4287106519122686,0.323302003519649

NanoBEIR_evaluation_mean_results.csv

@@ -18,3 +18,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.4639246467817896,0.6381789638932496,0.7059968602825747,0.7999372056514915,0.4639246467817896,0.2574883416047858,0.28848770277341707,0.3967121365566854,0.2275604395604396,0.46334885763578526,0.157701726844584,0.5507731361406536,0.5702974010116868,0.4993937412409821,0.41882901506085035
 -1,-1,0.5347880690737834,0.6966405023547881,0.7597802197802198,0.8415070643642071,0.5347880690737834,0.3146780556111113,0.31155416012558873,0.4549187058418722,0.2425934065934066,0.5222292120818444,0.16570172684458398,0.5950921301303091,0.6331734195509706,0.555988172340117,0.4770806248897853
 -1,-1,0.5070957613814757,0.6796860282574568,0.7551334379905809,0.8337519623233909,0.5070957613814757,0.2894853665744655,0.3162323390894819,0.44026914042866283,0.24290109890109893,0.5090244675056611,0.16491993720565146,0.5822769182556955,0.6107721462211259,0.5372799982578097,0.455213704756793
+-1,-1,0.4269387755102041,0.6074097331240188,0.6735949764521194,0.7522135007849293,0.4269387755102041,0.23895574840811443,0.27104133961276816,0.37409779039660057,0.21208163265306126,0.4292302560070531,0.14627315541601255,0.5087767504357891,0.5320760509331938,0.46132442631369514,0.3829122106534149

config.json

@@ -15,7 +15,7 @@
   "max_position_embeddings": 512,
   "model_type": "bert",
   "num_attention_heads": 12,
-  "num_hidden_layers": 6,
+  "num_hidden_layers": 12,
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
   "transformers_version": "4.57.3",

eval/Information-Retrieval_evaluation_NanoMSMARCO_results.csv

@@ -235,3 +235,10 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 2.4893314366998576,1750,0.36,0.54,0.58,0.72,0.36,0.36,0.18,0.54,0.11599999999999999,0.58,0.07200000000000001,0.72,0.4729126984126984,0.5317075196914398,0.48450217103749715
 2.844950213371266,2000,0.34,0.58,0.6,0.7,0.34,0.34,0.19333333333333333,0.58,0.12,0.6,0.07,0.7,0.46972222222222215,0.5258832154798058,0.48240881431376104
 3.200568990042674,2250,0.3,0.58,0.6,0.7,0.3,0.3,0.19333333333333333,0.58,0.12,0.6,0.07,0.7,0.44874603174603167,0.5101349275378135,0.4606212065533731
+0,0,0.38,0.62,0.68,0.8,0.38,0.38,0.20666666666666667,0.62,0.136,0.68,0.08,0.8,0.5215238095238095,0.5887227948760404,0.5325402082997991
+0.35561877667140823,250,0.3,0.5,0.62,0.72,0.3,0.3,0.16666666666666669,0.5,0.124,0.62,0.07200000000000001,0.72,0.42938095238095236,0.49899189472893807,0.4414443382127734
+0.7112375533428165,500,0.4,0.56,0.64,0.72,0.4,0.4,0.18666666666666668,0.56,0.128,0.64,0.07200000000000001,0.72,0.49943650793650796,0.5523338557685676,0.5124687546715411
+1.0668563300142249,750,0.36,0.56,0.68,0.76,0.36,0.36,0.18666666666666668,0.56,0.136,0.68,0.07600000000000001,0.76,0.48572222222222217,0.5517516200981174,0.4972642669780404
+1.422475106685633,1000,0.36,0.58,0.66,0.76,0.36,0.36,0.19333333333333333,0.58,0.132,0.66,0.07600000000000001,0.76,0.48749999999999993,0.5528646729879835,0.49795590132761597
+1.7780938833570412,1250,0.34,0.58,0.64,0.72,0.34,0.34,0.19333333333333333,0.58,0.128,0.64,0.07200000000000001,0.72,0.4674999999999999,0.5287566904972468,0.48136252648416433
+2.1337126600284497,1500,0.34,0.56,0.64,0.74,0.34,0.34,0.18666666666666668,0.56,0.128,0.64,0.07400000000000001,0.74,0.47276190476190466,0.5374407455925777,0.48561801675925215

eval/Information-Retrieval_evaluation_NanoNQ_results.csv

@@ -235,3 +235,10 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 2.4893314366998576,1750,0.28,0.46,0.54,0.6,0.28,0.26,0.15333333333333332,0.42,0.11200000000000002,0.51,0.06400000000000002,0.58,0.38766666666666666,0.42359029898899814,0.3820994852636087
 2.844950213371266,2000,0.3,0.48,0.52,0.6,0.3,0.28,0.16666666666666663,0.45,0.10800000000000001,0.49,0.066,0.59,0.4022460317460317,0.438878930103958,0.39908533175738836
 3.200568990042674,2250,0.28,0.48,0.52,0.58,0.28,0.26,0.16,0.44,0.11200000000000002,0.5,0.06400000000000002,0.57,0.3893888888888889,0.42522283720602283,0.38784914899138384
+0,0,0.44,0.62,0.7,0.72,0.44,0.42,0.20666666666666664,0.59,0.15200000000000002,0.69,0.07800000000000001,0.71,0.5425,0.5785694545006416,0.5396412232598975
+0.35561877667140823,250,0.4,0.52,0.58,0.68,0.4,0.38,0.18,0.49,0.124,0.56,0.07400000000000001,0.65,0.4802460317460317,0.5159372944131977,0.4812966031356987
+0.7112375533428165,500,0.34,0.5,0.6,0.66,0.34,0.33,0.16666666666666663,0.47,0.12400000000000003,0.57,0.07200000000000001,0.64,0.43333333333333335,0.47904748040828465,0.4343484137444015
+1.0668563300142249,750,0.32,0.48,0.58,0.64,0.32,0.3,0.16666666666666663,0.46,0.12,0.55,0.068,0.61,0.417,0.4577035422383739,0.417943646833548
+1.422475106685633,1000,0.42,0.52,0.58,0.66,0.42,0.39,0.18666666666666665,0.5,0.124,0.56,0.07200000000000001,0.64,0.4852777777777777,0.5129550595376149,0.4778814511409428
+1.7780938833570412,1250,0.38,0.54,0.58,0.74,0.38,0.35,0.18666666666666665,0.51,0.124,0.56,0.078,0.7,0.48316666666666663,0.5212260491322842,0.46420563439206014
+2.1337126600284497,1500,0.4,0.5,0.56,0.7,0.4,0.37,0.1733333333333333,0.47,0.12,0.54,0.07400000000000001,0.66,0.47743650793650794,0.5075548380780193,0.46217171679843827

eval/NanoBEIR_evaluation_mean_results.csv

@@ -235,3 +235,10 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 2.4893314366998576,1750,0.32,0.5,0.56,0.6599999999999999,0.32,0.31,0.16666666666666666,0.48,0.114,0.5449999999999999,0.068,0.6499999999999999,0.4302896825396825,0.477648909340219,0.43330082815055293
 2.844950213371266,2000,0.32,0.53,0.56,0.6499999999999999,0.32,0.31000000000000005,0.18,0.515,0.114,0.5449999999999999,0.068,0.645,0.4359841269841269,0.4823810727918819,0.4407470730355747
 3.200568990042674,2250,0.29000000000000004,0.53,0.56,0.6399999999999999,0.29000000000000004,0.28,0.17666666666666667,0.51,0.116,0.55,0.067,0.635,0.4190674603174603,0.4676788823719182,0.42423517777237846
+0,0,0.41000000000000003,0.62,0.69,0.76,0.41000000000000003,0.4,0.20666666666666667,0.605,0.14400000000000002,0.685,0.07900000000000001,0.755,0.5320119047619047,0.583646124688341,0.5360907157798482
+0.35561877667140823,250,0.35,0.51,0.6,0.7,0.35,0.33999999999999997,0.17333333333333334,0.495,0.124,0.5900000000000001,0.07300000000000001,0.685,0.45481349206349203,0.5074645945710679,0.4613704706742361
+0.7112375533428165,500,0.37,0.53,0.62,0.69,0.37,0.365,0.17666666666666664,0.515,0.126,0.605,0.07200000000000001,0.6799999999999999,0.46638492063492065,0.5156906680884261,0.4734085842079713
+1.0668563300142249,750,0.33999999999999997,0.52,0.63,0.7,0.33999999999999997,0.32999999999999996,0.17666666666666664,0.51,0.128,0.615,0.07200000000000001,0.685,0.4513611111111111,0.5047275811682457,0.4576039569057942
+1.422475106685633,1000,0.39,0.55,0.62,0.71,0.39,0.375,0.19,0.54,0.128,0.6100000000000001,0.07400000000000001,0.7,0.4863888888888888,0.5329098662627991,0.4879186762342794
+1.7780938833570412,1250,0.36,0.56,0.61,0.73,0.36,0.345,0.19,0.5449999999999999,0.126,0.6000000000000001,0.07500000000000001,0.71,0.4753333333333333,0.5249913698147655,0.47278408043811226
+2.1337126600284497,1500,0.37,0.53,0.6000000000000001,0.72,0.37,0.355,0.18,0.515,0.124,0.5900000000000001,0.07400000000000001,0.7,0.4750992063492063,0.5224977918352984,0.4738948667788452

final_metrics.json

@@ -1,231 +1,231 @@
 {
   "nano_beir": {
-    "NanoClimateFEVER_cosine_accuracy@1": 0.28,
-    "NanoClimateFEVER_cosine_accuracy@3": 0.5,
-    "NanoClimateFEVER_cosine_accuracy@5": 0.64,
-    "NanoClimateFEVER_cosine_accuracy@10": 0.7,
-    "NanoClimateFEVER_cosine_precision@1": 0.28,
-    "NanoClimateFEVER_cosine_precision@3": 0.18666666666666665,
-    "NanoClimateFEVER_cosine_precision@5": 0.14800000000000002,
-    "NanoClimateFEVER_cosine_precision@10": 0.08199999999999999,
-    "NanoClimateFEVER_cosine_recall@1": 0.12333333333333332,
-    "NanoClimateFEVER_cosine_recall@3": 0.24333333333333332,
-    "NanoClimateFEVER_cosine_recall@5": 0.31566666666666665,
-    "NanoClimateFEVER_cosine_recall@10": 0.3423333333333333,
-    "NanoClimateFEVER_cosine_ndcg@10": 0.2907447124874634,
-    "NanoClimateFEVER_cosine_mrr@10": 0.41155555555555556,
-    "NanoClimateFEVER_cosine_map@100": 0.22664092730177512,
-    "NanoDBPedia_cosine_accuracy@1": 0.72,
-    "NanoDBPedia_cosine_accuracy@3": 0.88,
-    "NanoDBPedia_cosine_accuracy@5": 0.88,
-    "NanoDBPedia_cosine_accuracy@10": 0.94,
-    "NanoDBPedia_cosine_precision@1": 0.72,
-    "NanoDBPedia_cosine_precision@3": 0.5533333333333333,
-    "NanoDBPedia_cosine_precision@5": 0.4600000000000001,
-    "NanoDBPedia_cosine_precision@10": 0.386,
-    "NanoDBPedia_cosine_recall@1": 0.0837828590640337,
-    "NanoDBPedia_cosine_recall@3": 0.16110714540075896,
-    "NanoDBPedia_cosine_recall@5": 0.19518511267382124,
-    "NanoDBPedia_cosine_recall@10": 0.2697616826690356,
-    "NanoDBPedia_cosine_ndcg@10": 0.5084374485621219,
-    "NanoDBPedia_cosine_mrr@10": 0.7983333333333335,
-    "NanoDBPedia_cosine_map@100": 0.3354481672493977,
-    "NanoFEVER_cosine_accuracy@1": 0.78,
-    "NanoFEVER_cosine_accuracy@3": 0.98,
-    "NanoFEVER_cosine_accuracy@5": 0.98,
-    "NanoFEVER_cosine_accuracy@10": 0.98,
-    "NanoFEVER_cosine_precision@1": 0.78,
-    "NanoFEVER_cosine_precision@3": 0.32666666666666666,
-    "NanoFEVER_cosine_precision@5": 0.19999999999999996,
-    "NanoFEVER_cosine_precision@10": 0.09999999999999998,
-    "NanoFEVER_cosine_recall@1": 0.7366666666666666,
-    "NanoFEVER_cosine_recall@3": 0.9166666666666667,
-    "NanoFEVER_cosine_recall@5": 0.9266666666666667,
-    "NanoFEVER_cosine_recall@10": 0.9266666666666667,
-    "NanoFEVER_cosine_ndcg@10": 0.8547856660415037,
-    "NanoFEVER_cosine_mrr@10": 0.8633333333333332,
-    "NanoFEVER_cosine_map@100": 0.8163245045176333,
-    "NanoFiQA2018_cosine_accuracy@1": 0.32,
-    "NanoFiQA2018_cosine_accuracy@3": 0.46,
-    "NanoFiQA2018_cosine_accuracy@5": 0.6,
+    "NanoClimateFEVER_cosine_accuracy@1": 0.26,
+    "NanoClimateFEVER_cosine_accuracy@3": 0.36,
+    "NanoClimateFEVER_cosine_accuracy@5": 0.44,
+    "NanoClimateFEVER_cosine_accuracy@10": 0.52,
+    "NanoClimateFEVER_cosine_precision@1": 0.26,
+    "NanoClimateFEVER_cosine_precision@3": 0.12,
+    "NanoClimateFEVER_cosine_precision@5": 0.092,
+    "NanoClimateFEVER_cosine_precision@10": 0.062,
+    "NanoClimateFEVER_cosine_recall@1": 0.14166666666666666,
+    "NanoClimateFEVER_cosine_recall@3": 0.19,
+    "NanoClimateFEVER_cosine_recall@5": 0.22333333333333336,
+    "NanoClimateFEVER_cosine_recall@10": 0.2723333333333333,
+    "NanoClimateFEVER_cosine_ndcg@10": 0.2436767141441193,
+    "NanoClimateFEVER_cosine_mrr@10": 0.33557936507936503,
+    "NanoClimateFEVER_cosine_map@100": 0.20217806834795687,
+    "NanoDBPedia_cosine_accuracy@1": 0.56,
+    "NanoDBPedia_cosine_accuracy@3": 0.8,
+    "NanoDBPedia_cosine_accuracy@5": 0.86,
+    "NanoDBPedia_cosine_accuracy@10": 0.9,
+    "NanoDBPedia_cosine_precision@1": 0.56,
+    "NanoDBPedia_cosine_precision@3": 0.5,
+    "NanoDBPedia_cosine_precision@5": 0.44,
+    "NanoDBPedia_cosine_precision@10": 0.35,
+    "NanoDBPedia_cosine_recall@1": 0.057167885222086164,
+    "NanoDBPedia_cosine_recall@3": 0.12515612374824867,
+    "NanoDBPedia_cosine_recall@5": 0.1822183603452181,
+    "NanoDBPedia_cosine_recall@10": 0.24167414201200188,
+    "NanoDBPedia_cosine_ndcg@10": 0.4445153910998771,
+    "NanoDBPedia_cosine_mrr@10": 0.6821904761904762,
+    "NanoDBPedia_cosine_map@100": 0.276586633736675,
+    "NanoFEVER_cosine_accuracy@1": 0.62,
+    "NanoFEVER_cosine_accuracy@3": 0.8,
+    "NanoFEVER_cosine_accuracy@5": 0.86,
+    "NanoFEVER_cosine_accuracy@10": 0.9,
+    "NanoFEVER_cosine_precision@1": 0.62,
+    "NanoFEVER_cosine_precision@3": 0.2733333333333333,
+    "NanoFEVER_cosine_precision@5": 0.18,
+    "NanoFEVER_cosine_precision@10": 0.09399999999999999,
+    "NanoFEVER_cosine_recall@1": 0.5866666666666667,
+    "NanoFEVER_cosine_recall@3": 0.7533333333333333,
+    "NanoFEVER_cosine_recall@5": 0.8133333333333332,
+    "NanoFEVER_cosine_recall@10": 0.8533333333333333,
+    "NanoFEVER_cosine_ndcg@10": 0.7336687791965945,
+    "NanoFEVER_cosine_mrr@10": 0.7168571428571429,
+    "NanoFEVER_cosine_map@100": 0.687890775890776,
+    "NanoFiQA2018_cosine_accuracy@1": 0.34,
+    "NanoFiQA2018_cosine_accuracy@3": 0.48,
+    "NanoFiQA2018_cosine_accuracy@5": 0.54,
     "NanoFiQA2018_cosine_accuracy@10": 0.68,
-    "NanoFiQA2018_cosine_precision@1": 0.32,
-    "NanoFiQA2018_cosine_precision@3": 0.19333333333333333,
-    "NanoFiQA2018_cosine_precision@5": 0.16,
+    "NanoFiQA2018_cosine_precision@1": 0.34,
+    "NanoFiQA2018_cosine_precision@3": 0.18,
+    "NanoFiQA2018_cosine_precision@5": 0.14,
     "NanoFiQA2018_cosine_precision@10": 0.09599999999999997,
-    "NanoFiQA2018_cosine_recall@1": 0.1880793650793651,
-    "NanoFiQA2018_cosine_recall@3": 0.2747698412698413,
-    "NanoFiQA2018_cosine_recall@5": 0.3924365079365079,
-    "NanoFiQA2018_cosine_recall@10": 0.46096031746031746,
-    "NanoFiQA2018_cosine_ndcg@10": 0.3645000219538997,
-    "NanoFiQA2018_cosine_mrr@10": 0.4274920634920635,
-    "NanoFiQA2018_cosine_map@100": 0.29800480481282754,
-    "NanoHotpotQA_cosine_accuracy@1": 0.74,
-    "NanoHotpotQA_cosine_accuracy@3": 0.84,
-    "NanoHotpotQA_cosine_accuracy@5": 0.86,
-    "NanoHotpotQA_cosine_accuracy@10": 0.88,
-    "NanoHotpotQA_cosine_precision@1": 0.74,
-    "NanoHotpotQA_cosine_precision@3": 0.38666666666666666,
-    "NanoHotpotQA_cosine_precision@5": 0.248,
-    "NanoHotpotQA_cosine_precision@10": 0.12999999999999998,
-    "NanoHotpotQA_cosine_recall@1": 0.37,
-    "NanoHotpotQA_cosine_recall@3": 0.58,
-    "NanoHotpotQA_cosine_recall@5": 0.62,
-    "NanoHotpotQA_cosine_recall@10": 0.65,
-    "NanoHotpotQA_cosine_ndcg@10": 0.6362626999276922,
-    "NanoHotpotQA_cosine_mrr@10": 0.7873333333333333,
-    "NanoHotpotQA_cosine_map@100": 0.5727077888418632,
-    "NanoMSMARCO_cosine_accuracy@1": 0.32,
-    "NanoMSMARCO_cosine_accuracy@3": 0.56,
-    "NanoMSMARCO_cosine_accuracy@5": 0.66,
-    "NanoMSMARCO_cosine_accuracy@10": 0.76,
-    "NanoMSMARCO_cosine_precision@1": 0.32,
-    "NanoMSMARCO_cosine_precision@3": 0.18666666666666668,
-    "NanoMSMARCO_cosine_precision@5": 0.132,
-    "NanoMSMARCO_cosine_precision@10": 0.07600000000000001,
-    "NanoMSMARCO_cosine_recall@1": 0.32,
-    "NanoMSMARCO_cosine_recall@3": 0.56,
-    "NanoMSMARCO_cosine_recall@5": 0.66,
-    "NanoMSMARCO_cosine_recall@10": 0.76,
-    "NanoMSMARCO_cosine_ndcg@10": 0.543482168903518,
-    "NanoMSMARCO_cosine_mrr@10": 0.474047619047619,
-    "NanoMSMARCO_cosine_map@100": 0.48355956186670473,
+    "NanoFiQA2018_cosine_recall@1": 0.17952380952380953,
+    "NanoFiQA2018_cosine_recall@3": 0.27874603174603174,
+    "NanoFiQA2018_cosine_recall@5": 0.33376984126984127,
+    "NanoFiQA2018_cosine_recall@10": 0.4741587301587301,
+    "NanoFiQA2018_cosine_ndcg@10": 0.3576193898882579,
+    "NanoFiQA2018_cosine_mrr@10": 0.43,
+    "NanoFiQA2018_cosine_map@100": 0.28259055809600414,
+    "NanoHotpotQA_cosine_accuracy@1": 0.48,
+    "NanoHotpotQA_cosine_accuracy@3": 0.64,
+    "NanoHotpotQA_cosine_accuracy@5": 0.72,
+    "NanoHotpotQA_cosine_accuracy@10": 0.78,
+    "NanoHotpotQA_cosine_precision@1": 0.48,
+    "NanoHotpotQA_cosine_precision@3": 0.24666666666666665,
+    "NanoHotpotQA_cosine_precision@5": 0.17199999999999996,
+    "NanoHotpotQA_cosine_precision@10": 0.09799999999999999,
+    "NanoHotpotQA_cosine_recall@1": 0.24,
+    "NanoHotpotQA_cosine_recall@3": 0.37,
+    "NanoHotpotQA_cosine_recall@5": 0.43,
+    "NanoHotpotQA_cosine_recall@10": 0.49,
+    "NanoHotpotQA_cosine_ndcg@10": 0.4426260898247735,
+    "NanoHotpotQA_cosine_mrr@10": 0.5775238095238096,
+    "NanoHotpotQA_cosine_map@100": 0.36293313513648634,
+    "NanoMSMARCO_cosine_accuracy@1": 0.3,
+    "NanoMSMARCO_cosine_accuracy@3": 0.58,
+    "NanoMSMARCO_cosine_accuracy@5": 0.6,
+    "NanoMSMARCO_cosine_accuracy@10": 0.7,
+    "NanoMSMARCO_cosine_precision@1": 0.3,
+    "NanoMSMARCO_cosine_precision@3": 0.19333333333333333,
+    "NanoMSMARCO_cosine_precision@5": 0.12,
+    "NanoMSMARCO_cosine_precision@10": 0.07,
+    "NanoMSMARCO_cosine_recall@1": 0.3,
+    "NanoMSMARCO_cosine_recall@3": 0.58,
+    "NanoMSMARCO_cosine_recall@5": 0.6,
+    "NanoMSMARCO_cosine_recall@10": 0.7,
+    "NanoMSMARCO_cosine_ndcg@10": 0.5101349275378135,
+    "NanoMSMARCO_cosine_mrr@10": 0.44874603174603167,
+    "NanoMSMARCO_cosine_map@100": 0.4606212065533731,
     "NanoNFCorpus_cosine_accuracy@1": 0.36,
-    "NanoNFCorpus_cosine_accuracy@3": 0.5,
-    "NanoNFCorpus_cosine_accuracy@5": 0.56,
-    "NanoNFCorpus_cosine_accuracy@10": 0.68,
+    "NanoNFCorpus_cosine_accuracy@3": 0.42,
+    "NanoNFCorpus_cosine_accuracy@5": 0.58,
+    "NanoNFCorpus_cosine_accuracy@10": 0.62,
     "NanoNFCorpus_cosine_precision@1": 0.36,
-    "NanoNFCorpus_cosine_precision@3": 0.3533333333333333,
-    "NanoNFCorpus_cosine_precision@5": 0.32,
-    "NanoNFCorpus_cosine_precision@10": 0.284,
-    "NanoNFCorpus_cosine_recall@1": 0.011117260803746984,
-    "NanoNFCorpus_cosine_recall@3": 0.06793780077947238,
-    "NanoNFCorpus_cosine_recall@5": 0.08600906529821184,
-    "NanoNFCorpus_cosine_recall@10": 0.12489478806450519,
-    "NanoNFCorpus_cosine_ndcg@10": 0.31419371833661064,
-    "NanoNFCorpus_cosine_mrr@10": 0.4486904761904762,
-    "NanoNFCorpus_cosine_map@100": 0.1305557027672931,
-    "NanoNQ_cosine_accuracy@1": 0.42,
-    "NanoNQ_cosine_accuracy@3": 0.56,
-    "NanoNQ_cosine_accuracy@5": 0.6,
-    "NanoNQ_cosine_accuracy@10": 0.76,
-    "NanoNQ_cosine_precision@1": 0.42,
-    "NanoNQ_cosine_precision@3": 0.2,
-    "NanoNQ_cosine_precision@5": 0.132,
-    "NanoNQ_cosine_precision@10": 0.08199999999999999,
-    "NanoNQ_cosine_recall@1": 0.39,
-    "NanoNQ_cosine_recall@3": 0.55,
-    "NanoNQ_cosine_recall@5": 0.59,
-    "NanoNQ_cosine_recall@10": 0.74,
-    "NanoNQ_cosine_ndcg@10": 0.5531504219817556,
-    "NanoNQ_cosine_mrr@10": 0.5029365079365079,
-    "NanoNQ_cosine_map@100": 0.5003951480571269,
-    "NanoQuoraRetrieval_cosine_accuracy@1": 0.82,
+    "NanoNFCorpus_cosine_precision@3": 0.2866666666666666,
+    "NanoNFCorpus_cosine_precision@5": 0.304,
+    "NanoNFCorpus_cosine_precision@10": 0.242,
+    "NanoNFCorpus_cosine_recall@1": 0.011413047310317982,
+    "NanoNFCorpus_cosine_recall@3": 0.02700258816152921,
+    "NanoNFCorpus_cosine_recall@5": 0.04979610755705784,
+    "NanoNFCorpus_cosine_recall@10": 0.07563880594353418,
+    "NanoNFCorpus_cosine_ndcg@10": 0.2645713317352105,
+    "NanoNFCorpus_cosine_mrr@10": 0.43044444444444446,
+    "NanoNFCorpus_cosine_map@100": 0.08670541591415526,
+    "NanoNQ_cosine_accuracy@1": 0.28,
+    "NanoNQ_cosine_accuracy@3": 0.48,
+    "NanoNQ_cosine_accuracy@5": 0.52,
+    "NanoNQ_cosine_accuracy@10": 0.58,
+    "NanoNQ_cosine_precision@1": 0.28,
+    "NanoNQ_cosine_precision@3": 0.16,
+    "NanoNQ_cosine_precision@5": 0.11200000000000002,
+    "NanoNQ_cosine_precision@10": 0.06400000000000002,
+    "NanoNQ_cosine_recall@1": 0.26,
+    "NanoNQ_cosine_recall@3": 0.44,
+    "NanoNQ_cosine_recall@5": 0.5,
+    "NanoNQ_cosine_recall@10": 0.57,
+    "NanoNQ_cosine_ndcg@10": 0.42522283720602283,
+    "NanoNQ_cosine_mrr@10": 0.3893888888888889,
+    "NanoNQ_cosine_map@100": 0.38784914899138384,
+    "NanoQuoraRetrieval_cosine_accuracy@1": 0.8,
     "NanoQuoraRetrieval_cosine_accuracy@3": 0.94,
     "NanoQuoraRetrieval_cosine_accuracy@5": 0.94,
     "NanoQuoraRetrieval_cosine_accuracy@10": 0.96,
-    "NanoQuoraRetrieval_cosine_precision@1": 0.82,
-    "NanoQuoraRetrieval_cosine_precision@3": 0.3933333333333333,
+    "NanoQuoraRetrieval_cosine_precision@1": 0.8,
+    "NanoQuoraRetrieval_cosine_precision@3": 0.3999999999999999,
     "NanoQuoraRetrieval_cosine_precision@5": 0.24799999999999997,
     "NanoQuoraRetrieval_cosine_precision@10": 0.12999999999999998,
-    "NanoQuoraRetrieval_cosine_recall@1": 0.7073333333333331,
-    "NanoQuoraRetrieval_cosine_recall@3": 0.9053333333333333,
-    "NanoQuoraRetrieval_cosine_recall@5": 0.9226666666666666,
+    "NanoQuoraRetrieval_cosine_recall@1": 0.6873333333333334,
+    "NanoQuoraRetrieval_cosine_recall@3": 0.9086666666666667,
+    "NanoQuoraRetrieval_cosine_recall@5": 0.922,
     "NanoQuoraRetrieval_cosine_recall@10": 0.95,
-    "NanoQuoraRetrieval_cosine_ndcg@10": 0.8855845442596749,
-    "NanoQuoraRetrieval_cosine_mrr@10": 0.8761904761904762,
-    "NanoQuoraRetrieval_cosine_map@100": 0.8602467532467531,
+    "NanoQuoraRetrieval_cosine_ndcg@10": 0.8827689846162723,
+    "NanoQuoraRetrieval_cosine_mrr@10": 0.8691666666666668,
+    "NanoQuoraRetrieval_cosine_map@100": 0.8574092460390633,
     "NanoSCIDOCS_cosine_accuracy@1": 0.5,
-    "NanoSCIDOCS_cosine_accuracy@3": 0.7,
-    "NanoSCIDOCS_cosine_accuracy@5": 0.84,
-    "NanoSCIDOCS_cosine_accuracy@10": 0.9,
+    "NanoSCIDOCS_cosine_accuracy@3": 0.68,
+    "NanoSCIDOCS_cosine_accuracy@5": 0.74,
+    "NanoSCIDOCS_cosine_accuracy@10": 0.8,
     "NanoSCIDOCS_cosine_precision@1": 0.5,
-    "NanoSCIDOCS_cosine_precision@3": 0.38,
-    "NanoSCIDOCS_cosine_precision@5": 0.324,
-    "NanoSCIDOCS_cosine_precision@10": 0.20199999999999999,
-    "NanoSCIDOCS_cosine_recall@1": 0.10466666666666667,
-    "NanoSCIDOCS_cosine_recall@3": 0.23366666666666666,
-    "NanoSCIDOCS_cosine_recall@5": 0.33166666666666667,
-    "NanoSCIDOCS_cosine_recall@10": 0.4126666666666667,
-    "NanoSCIDOCS_cosine_ndcg@10": 0.4094545669474307,
-    "NanoSCIDOCS_cosine_mrr@10": 0.6263571428571427,
-    "NanoSCIDOCS_cosine_map@100": 0.3236610548684944,
+    "NanoSCIDOCS_cosine_precision@3": 0.3399999999999999,
+    "NanoSCIDOCS_cosine_precision@5": 0.25599999999999995,
+    "NanoSCIDOCS_cosine_precision@10": 0.16799999999999998,
+    "NanoSCIDOCS_cosine_recall@1": 0.10200000000000001,
+    "NanoSCIDOCS_cosine_recall@3": 0.2096666666666666,
+    "NanoSCIDOCS_cosine_recall@5": 0.2626666666666666,
+    "NanoSCIDOCS_cosine_recall@10": 0.3436666666666666,
+    "NanoSCIDOCS_cosine_ndcg@10": 0.3562789819319996,
+    "NanoSCIDOCS_cosine_mrr@10": 0.602079365079365,
+    "NanoSCIDOCS_cosine_map@100": 0.27946780160236867,
     "NanoArguAna_cosine_accuracy@1": 0.2,
-    "NanoArguAna_cosine_accuracy@3": 0.44,
-    "NanoArguAna_cosine_accuracy@5": 0.66,
-    "NanoArguAna_cosine_accuracy@10": 0.82,
+    "NanoArguAna_cosine_accuracy@3": 0.4,
+    "NanoArguAna_cosine_accuracy@5": 0.58,
+    "NanoArguAna_cosine_accuracy@10": 0.76,
     "NanoArguAna_cosine_precision@1": 0.2,
-    "NanoArguAna_cosine_precision@3": 0.14666666666666664,
-    "NanoArguAna_cosine_precision@5": 0.132,
-    "NanoArguAna_cosine_precision@10": 0.08199999999999999,
+    "NanoArguAna_cosine_precision@3": 0.13333333333333333,
+    "NanoArguAna_cosine_precision@5": 0.11600000000000002,
+    "NanoArguAna_cosine_precision@10": 0.07600000000000001,
     "NanoArguAna_cosine_recall@1": 0.2,
-    "NanoArguAna_cosine_recall@3": 0.44,
-    "NanoArguAna_cosine_recall@5": 0.66,
-    "NanoArguAna_cosine_recall@10": 0.82,
-    "NanoArguAna_cosine_ndcg@10": 0.4889503790004362,
-    "NanoArguAna_cosine_mrr@10": 0.3852460317460317,
-    "NanoArguAna_cosine_map@100": 0.3927867585630743,
-    "NanoSciFact_cosine_accuracy@1": 0.52,
-    "NanoSciFact_cosine_accuracy@3": 0.68,
-    "NanoSciFact_cosine_accuracy@5": 0.76,
-    "NanoSciFact_cosine_accuracy@10": 0.84,
-    "NanoSciFact_cosine_precision@1": 0.52,
-    "NanoSciFact_cosine_precision@3": 0.2533333333333333,
-    "NanoSciFact_cosine_precision@5": 0.16799999999999998,
-    "NanoSciFact_cosine_precision@10": 0.09599999999999997,
-    "NanoSciFact_cosine_recall@1": 0.485,
-    "NanoSciFact_cosine_recall@3": 0.675,
-    "NanoSciFact_cosine_recall@5": 0.745,
-    "NanoSciFact_cosine_recall@10": 0.84,
-    "NanoSciFact_cosine_ndcg@10": 0.671924698303424,
-    "NanoSciFact_cosine_mrr@10": 0.6191666666666666,
-    "NanoSciFact_cosine_map@100": 0.62085644979463,
-    "NanoTouche2020_cosine_accuracy@1": 0.6122448979591837,
-    "NanoTouche2020_cosine_accuracy@3": 0.7959183673469388,
+    "NanoArguAna_cosine_recall@3": 0.4,
+    "NanoArguAna_cosine_recall@5": 0.58,
+    "NanoArguAna_cosine_recall@10": 0.76,
+    "NanoArguAna_cosine_ndcg@10": 0.445906963986827,
+    "NanoArguAna_cosine_mrr@10": 0.3499444444444444,
+    "NanoArguAna_cosine_map@100": 0.3549188614872763,
+    "NanoSciFact_cosine_accuracy@1": 0.34,
+    "NanoSciFact_cosine_accuracy@3": 0.5,
+    "NanoSciFact_cosine_accuracy@5": 0.54,
+    "NanoSciFact_cosine_accuracy@10": 0.64,
+    "NanoSciFact_cosine_precision@1": 0.34,
+    "NanoSciFact_cosine_precision@3": 0.18,
+    "NanoSciFact_cosine_precision@5": 0.12400000000000003,
+    "NanoSciFact_cosine_precision@10": 0.07400000000000001,
+    "NanoSciFact_cosine_recall@1": 0.305,
+    "NanoSciFact_cosine_recall@3": 0.47,
+    "NanoSciFact_cosine_recall@5": 0.52,
+    "NanoSciFact_cosine_recall@10": 0.63,
+    "NanoSciFact_cosine_ndcg@10": 0.4615164989979999,
+    "NanoSciFact_cosine_mrr@10": 0.42055555555555557,
+    "NanoSciFact_cosine_map@100": 0.41540588317922533,
+    "NanoTouche2020_cosine_accuracy@1": 0.5102040816326531,
+    "NanoTouche2020_cosine_accuracy@3": 0.8163265306122449,
     "NanoTouche2020_cosine_accuracy@5": 0.8367346938775511,
     "NanoTouche2020_cosine_accuracy@10": 0.9387755102040817,
-    "NanoTouche2020_cosine_precision@1": 0.6122448979591837,
-    "NanoTouche2020_cosine_precision@3": 0.5510204081632653,
-    "NanoTouche2020_cosine_precision@5": 0.4857142857142857,
-    "NanoTouche2020_cosine_precision@10": 0.3979591836734694,
-    "NanoTouche2020_cosine_recall@1": 0.0433302805209062,
-    "NanoTouche2020_cosine_recall@3": 0.11568403812254441,
-    "NanoTouche2020_cosine_recall@5": 0.1720207249983863,
-    "NanoTouche2020_cosine_recall@10": 0.2723164824635157,
-    "NanoTouche2020_cosine_ndcg@10": 0.4631689306459952,
-    "NanoTouche2020_cosine_mrr@10": 0.719355361192096,
-    "NanoTouche2020_cosine_map@100": 0.3565905399507358,
-    "NanoBEIR_mean_cosine_accuracy@1": 0.5070957613814757,
-    "NanoBEIR_mean_cosine_accuracy@3": 0.6796860282574568,
-    "NanoBEIR_mean_cosine_accuracy@5": 0.7551334379905809,
-    "NanoBEIR_mean_cosine_accuracy@10": 0.8337519623233909,
-    "NanoBEIR_mean_cosine_precision@1": 0.5070957613814757,
-    "NanoBEIR_mean_cosine_precision@3": 0.3162323390894819,
-    "NanoBEIR_mean_cosine_precision@5": 0.24290109890109893,
-    "NanoBEIR_mean_cosine_precision@10": 0.16491993720565146,
-    "NanoBEIR_mean_cosine_recall@1": 0.2894853665744655,
-    "NanoBEIR_mean_cosine_recall@3": 0.44026914042866283,
-    "NanoBEIR_mean_cosine_recall@5": 0.5090244675056611,
-    "NanoBEIR_mean_cosine_recall@10": 0.5822769182556955,
-    "NanoBEIR_mean_cosine_ndcg@10": 0.5372799982578097,
-    "NanoBEIR_mean_cosine_mrr@10": 0.6107721462211259,
-    "NanoBEIR_mean_cosine_map@100": 0.455213704756793
+    "NanoTouche2020_cosine_precision@1": 0.5102040816326531,
+    "NanoTouche2020_cosine_precision@3": 0.510204081632653,
+    "NanoTouche2020_cosine_precision@5": 0.4530612244897959,
+    "NanoTouche2020_cosine_precision@10": 0.37755102040816324,
+    "NanoTouche2020_cosine_recall@1": 0.035653320582606944,
+    "NanoTouche2020_cosine_recall@3": 0.11069986483333172,
+    "NanoTouche2020_cosine_recall@5": 0.16287568558624005,
+    "NanoTouche2020_cosine_recall@10": 0.25329274421765885,
+    "NanoTouche2020_cosine_ndcg@10": 0.4287106519122686,
+    "NanoTouche2020_cosine_mrr@10": 0.6645124716553287,
+    "NanoTouche2020_cosine_map@100": 0.323302003519649,
+    "NanoBEIR_mean_cosine_accuracy@1": 0.4269387755102041,
+    "NanoBEIR_mean_cosine_accuracy@3": 0.6074097331240188,
+    "NanoBEIR_mean_cosine_accuracy@5": 0.6735949764521194,
+    "NanoBEIR_mean_cosine_accuracy@10": 0.7522135007849293,
+    "NanoBEIR_mean_cosine_precision@1": 0.4269387755102041,
+    "NanoBEIR_mean_cosine_precision@3": 0.27104133961276816,
+    "NanoBEIR_mean_cosine_precision@5": 0.21208163265306126,
+    "NanoBEIR_mean_cosine_precision@10": 0.14627315541601255,
+    "NanoBEIR_mean_cosine_recall@1": 0.23895574840811443,
+    "NanoBEIR_mean_cosine_recall@3": 0.37409779039660057,
+    "NanoBEIR_mean_cosine_recall@5": 0.4292302560070531,
+    "NanoBEIR_mean_cosine_recall@10": 0.5087767504357891,
+    "NanoBEIR_mean_cosine_ndcg@10": 0.46132442631369514,
+    "NanoBEIR_mean_cosine_mrr@10": 0.5320760509331938,
+    "NanoBEIR_mean_cosine_map@100": 0.3829122106534149
   },
   "beir_touche2020": {
-    "BeIR-touche2020-subset-test_cosine_accuracy@1": 0.7755102040816326,
-    "BeIR-touche2020-subset-test_cosine_accuracy@3": 0.9795918367346939,
-    "BeIR-touche2020-subset-test_cosine_accuracy@5": 1.0,
+    "BeIR-touche2020-subset-test_cosine_accuracy@1": 0.6938775510204082,
+    "BeIR-touche2020-subset-test_cosine_accuracy@3": 0.9591836734693877,
+    "BeIR-touche2020-subset-test_cosine_accuracy@5": 0.9591836734693877,
     "BeIR-touche2020-subset-test_cosine_accuracy@10": 1.0,
-    "BeIR-touche2020-subset-test_cosine_precision@1": 0.7755102040816326,
-    "BeIR-touche2020-subset-test_cosine_precision@3": 0.7551020408163265,
-    "BeIR-touche2020-subset-test_cosine_precision@5": 0.7265306122448978,
-    "BeIR-touche2020-subset-test_cosine_precision@10": 0.6571428571428573,
-    "BeIR-touche2020-subset-test_cosine_recall@1": 0.017161759287106504,
-    "BeIR-touche2020-subset-test_cosine_recall@3": 0.050083191794989906,
-    "BeIR-touche2020-subset-test_cosine_recall@5": 0.08004301263609473,
-    "BeIR-touche2020-subset-test_cosine_recall@10": 0.14521580076391974,
-    "BeIR-touche2020-subset-test_cosine_ndcg@10": 0.6892612517303571,
-    "BeIR-touche2020-subset-test_cosine_mrr@10": 0.8714285714285713,
-    "BeIR-touche2020-subset-test_cosine_map@100": 0.3065539748752648
+    "BeIR-touche2020-subset-test_cosine_precision@1": 0.6938775510204082,
+    "BeIR-touche2020-subset-test_cosine_precision@3": 0.7142857142857142,
+    "BeIR-touche2020-subset-test_cosine_precision@5": 0.6489795918367348,
+    "BeIR-touche2020-subset-test_cosine_precision@10": 0.5693877551020408,
+    "BeIR-touche2020-subset-test_cosine_recall@1": 0.01524437495344929,
+    "BeIR-touche2020-subset-test_cosine_recall@3": 0.047106170818450595,
+    "BeIR-touche2020-subset-test_cosine_recall@5": 0.07152292375348247,
+    "BeIR-touche2020-subset-test_cosine_recall@10": 0.125504336824092,
+    "BeIR-touche2020-subset-test_cosine_ndcg@10": 0.6061049268897444,
+    "BeIR-touche2020-subset-test_cosine_mrr@10": 0.8226433430515063,
+    "BeIR-touche2020-subset-test_cosine_map@100": 0.2612230144327072
   }
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e71abca91db03877030052c2d9b85bced7d6f8f79b15724b5d5b21f5fc5f0ac7
-size 90864192
+oid sha256:0500af9377f77d586384bdb50004177507ac045d8f0c21b99459899825e4b69f
+size 133462128

tokenizer_config.json

@@ -48,7 +48,7 @@
   "extra_special_tokens": {},
   "mask_token": "[MASK]",
   "max_length": 128,
-  "model_max_length": 256,
+  "model_max_length": 128,
   "never_split": null,
   "pad_to_multiple_of": null,
   "pad_token": "[PAD]",

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:efe55e15f9ea5ddd41154764e8afa2f611cbfbf4390117ac4b8f641a5fe9fbb9
+oid sha256:8b2a4e7f6c24ae5f1c5c4a6891aa239df9649be32f7b0edec0d4355871b611e8
 size 6161