Training in progress, step 3000

Information-Retrieval_evaluation_BeIR-touche2020-subset-test_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.8571428571428571,0.9591836734693877,0.9795918367346939,1.0,0.8571428571428571,0.01908806967820627,0.7346938775510202,0.048693838019696914,0.7265306122448978,0.08028463408781296,0.6408163265306123,0.1415188943073563,0.914795918367347,0.6816395015686102,0.310162966316103
 -1,-1,0.7551020408163265,0.9795918367346939,1.0,1.0,0.7551020408163265,0.016696610477154657,0.7482993197278911,0.0495370280636804,0.6979591836734693,0.07716047273988862,0.6367346938775511,0.14070481102580362,0.8656462585034015,0.6673567750756741,0.2931959091991125
 -1,-1,0.7346938775510204,0.9795918367346939,1.0,1.0,0.7346938775510204,0.01638254490984421,0.727891156462585,0.048596148261189916,0.7183673469387756,0.07960185791379523,0.6326530612244898,0.1400201362033687,0.8476190476190478,0.6620487941595593,0.30295778120799477
+-1,-1,0.8571428571428571,0.9795918367346939,1.0,1.0,0.8571428571428571,0.01898438501321,0.802721088435374,0.05323720714947885,0.7387755102040815,0.0818345425971837,0.6571428571428573,0.14545490934511227,0.9200680272108844,0.7018027446625917,0.30282137720059765

Information-Retrieval_evaluation_NanoArguAna_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.26,0.48,0.7,0.82,0.26,0.26,0.15999999999999998,0.48,0.14,0.7,0.08199999999999999,0.82,0.41623809523809513,0.5123148768673178,0.42363861671989744
 -1,-1,0.2,0.4,0.56,0.76,0.2,0.2,0.13333333333333333,0.4,0.11200000000000002,0.56,0.07600000000000001,0.76,0.3633412698412698,0.4572919447108344,0.3740939900046161
 -1,-1,0.22,0.52,0.74,0.9,0.22,0.22,0.17333333333333337,0.52,0.14800000000000002,0.74,0.08999999999999998,0.9,0.4237222222222221,0.5374400718050902,0.4303466788466788
+-1,-1,0.2,0.46,0.62,0.82,0.2,0.2,0.1533333333333333,0.46,0.124,0.62,0.08199999999999999,0.82,0.390611111111111,0.4933028735845294,0.3998066055743007

Information-Retrieval_evaluation_NanoClimateFEVER_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.26,0.46,0.54,0.66,0.26,0.11333333333333333,0.16,0.22733333333333333,0.11600000000000002,0.25566666666666665,0.078,0.33399999999999996,0.3836349206349206,0.27327833254097583,0.21034773466212264
 -1,-1,0.24,0.4,0.5,0.64,0.24,0.10833333333333332,0.13999999999999999,0.19566666666666666,0.11199999999999999,0.2573333333333333,0.08,0.33899999999999997,0.3442777777777778,0.26136153314966504,0.19758289583526598
 -1,-1,0.28,0.4,0.58,0.68,0.28,0.13499999999999998,0.14666666666666667,0.21,0.132,0.294,0.08399999999999999,0.35200000000000004,0.38588095238095227,0.29076885639822775,0.2284985743248978
+-1,-1,0.28,0.42,0.5,0.64,0.28,0.12666666666666665,0.15333333333333332,0.1973333333333333,0.11600000000000002,0.2606666666666666,0.07400000000000001,0.3123333333333333,0.37093650793650795,0.26290792445639205,0.2087000001335581

Information-Retrieval_evaluation_NanoDBPedia_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.7,0.84,0.88,0.96,0.7,0.05617827690815805,0.5266666666666666,0.13531139732706876,0.46800000000000014,0.17671248748276733,0.37400000000000005,0.2816880137027782,0.7866904761904762,0.4900946959983428,0.32701037668306887
 -1,-1,0.7,0.86,0.9,0.94,0.7,0.07744060964678427,0.5333333333333333,0.13432808008201974,0.4640000000000001,0.1886309205749346,0.36200000000000004,0.26436977888944535,0.7786666666666667,0.4822270933552821,0.3308160981806389
 -1,-1,0.68,0.84,0.9,0.96,0.68,0.05716747444864907,0.5466666666666667,0.1337308951341992,0.452,0.17566784068129068,0.37200000000000005,0.2632314620490831,0.7753333333333333,0.4849472222283775,0.3229143949554386
+-1,-1,0.64,0.82,0.86,0.9,0.64,0.06869625936429839,0.4799999999999999,0.12411529604858355,0.4159999999999999,0.1649095059218987,0.366,0.25973433711392624,0.7323809523809526,0.4696471920704787,0.31155113021441067

Information-Retrieval_evaluation_NanoFEVER_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.7,0.94,0.94,0.94,0.7,0.6466666666666666,0.3133333333333333,0.8766666666666667,0.19199999999999995,0.8866666666666667,0.09599999999999997,0.8866666666666667,0.7966666666666665,0.7929431596779439,0.75069227994228
 -1,-1,0.66,0.9,0.98,0.98,0.66,0.6166666666666667,0.30666666666666664,0.8466666666666667,0.19999999999999996,0.9266666666666667,0.09999999999999998,0.9266666666666667,0.7803333333333334,0.7937106761104978,0.737518312578003
 -1,-1,0.82,0.96,1.0,1.0,0.82,0.7566666666666667,0.32,0.8966666666666667,0.19999999999999996,0.9366666666666668,0.102,0.9466666666666668,0.8913333333333333,0.8736355301798917,0.8324328703703704
+-1,-1,0.8,0.96,0.96,0.98,0.8,0.7566666666666667,0.32666666666666666,0.9066666666666667,0.19599999999999995,0.9066666666666667,0.09999999999999998,0.9266666666666667,0.8728571428571429,0.862302442184373,0.827208000215349

Information-Retrieval_evaluation_NanoFiQA2018_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.36,0.56,0.68,0.72,0.36,0.20474603174603176,0.2333333333333333,0.3509603174603175,0.184,0.437015873015873,0.114,0.5040714285714286,0.47119047619047616,0.41187479499896335,0.34736633970220027
 -1,-1,0.44,0.6,0.68,0.74,0.44,0.23007936507936505,0.26,0.38646031746031745,0.192,0.4634603174603174,0.11800000000000001,0.5214047619047618,0.530111111111111,0.4416136713802792,0.37236608009347455
 -1,-1,0.4,0.62,0.64,0.7,0.4,0.21941269841269842,0.28,0.4022142857142857,0.19199999999999995,0.44707142857142856,0.11399999999999999,0.509626984126984,0.505,0.4352400324035161,0.3798068762112574
+-1,-1,0.38,0.48,0.56,0.62,0.38,0.2072460317460318,0.19333333333333336,0.3121031746031746,0.14,0.34743650793650793,0.088,0.4231031746031746,0.4389126984126985,0.35669365584544394,0.30271886425746414

Information-Retrieval_evaluation_NanoHotpotQA_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.58,0.72,0.8,0.86,0.58,0.29,0.29333333333333333,0.44,0.2,0.5,0.11599999999999998,0.58,0.6653333333333334,0.5271831752380164,0.4460418448413845
 -1,-1,0.66,0.76,0.82,0.86,0.66,0.33,0.33333333333333326,0.5,0.21599999999999994,0.54,0.12,0.6,0.7165,0.5663671505338735,0.4957705773369681
 -1,-1,0.8,0.86,0.9,0.92,0.8,0.4,0.4133333333333332,0.62,0.26799999999999996,0.67,0.13799999999999998,0.69,0.8385238095238097,0.6846067758620142,0.6229030032655473
+-1,-1,0.72,0.86,0.92,0.92,0.72,0.36,0.38666666666666666,0.58,0.272,0.68,0.144,0.72,0.7986666666666666,0.6741831390182679,0.5983102633770884

Information-Retrieval_evaluation_NanoMSMARCO_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.32,0.5,0.56,0.74,0.32,0.32,0.16666666666666669,0.5,0.11200000000000002,0.56,0.07400000000000001,0.74,0.4381269841269841,0.5084008935146356,0.4499550608678692
 -1,-1,0.34,0.56,0.68,0.76,0.34,0.34,0.18666666666666668,0.56,0.136,0.68,0.07600000000000001,0.76,0.4722222222222222,0.5416899912877863,0.48271862745098043
 -1,-1,0.44,0.7,0.72,0.84,0.44,0.44,0.2333333333333333,0.7,0.14400000000000002,0.72,0.084,0.84,0.5752380952380952,0.6393050305464907,0.5834313164313165
+-1,-1,0.32,0.56,0.62,0.74,0.32,0.32,0.18666666666666668,0.56,0.124,0.62,0.07400000000000001,0.74,0.4534126984126985,0.522258803283639,0.4638252994171221

Information-Retrieval_evaluation_NanoNFCorpus_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.34,0.5,0.62,0.74,0.34,0.010746681618306126,0.32,0.06426098047668373,0.3,0.08899281165704118,0.28200000000000003,0.12374847841340561,0.45521428571428574,0.3083182777163561,0.11785477160892308
 -1,-1,0.34,0.48,0.6,0.72,0.34,0.01228341125561172,0.32,0.052024850982170835,0.31199999999999994,0.08005972543817168,0.274,0.11726991771595457,0.4442460317460318,0.3007206174072767,0.11613626924932557
 -1,-1,0.4,0.5,0.56,0.68,0.4,0.017742022682771613,0.3466666666666666,0.04218740437276733,0.32,0.061297156728343155,0.282,0.10232183760818475,0.46851587301587294,0.3087896786838233,0.12702712283624432
+-1,-1,0.34,0.48,0.5,0.58,0.34,0.03047223530556736,0.33333333333333326,0.0543561699321758,0.292,0.06787885069496813,0.262,0.10337021977345857,0.4257142857142857,0.2963492902849603,0.12099779665938908

Information-Retrieval_evaluation_NanoNQ_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.42,0.56,0.6,0.62,0.42,0.4,0.2,0.55,0.132,0.59,0.068,0.61,0.4955555555555556,0.5222783108493494,0.5066931019396732
 -1,-1,0.44,0.56,0.6,0.66,0.44,0.42,0.2,0.54,0.132,0.59,0.07200000000000001,0.65,0.5043571428571428,0.5366135966288905,0.5082834994230612
 -1,-1,0.44,0.58,0.64,0.74,0.44,0.41,0.20666666666666664,0.56,0.14,0.63,0.08,0.71,0.5335555555555557,0.5669662624959938,0.5268891955660058
+-1,-1,0.32,0.54,0.54,0.74,0.32,0.29,0.18666666666666665,0.52,0.11600000000000002,0.53,0.07800000000000001,0.71,0.4477936507936508,0.49985826827052954,0.4354984725628689

Information-Retrieval_evaluation_NanoQuoraRetrieval_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.86,0.94,0.94,0.98,0.86,0.7473333333333332,0.38666666666666655,0.8986666666666667,0.24799999999999997,0.9226666666666666,0.13199999999999998,0.97,0.9061904761904762,0.9124260828303088,0.8898621553884712
 -1,-1,0.86,0.96,0.96,0.98,0.86,0.7473333333333332,0.4,0.9253333333333333,0.25199999999999995,0.9426666666666667,0.132,0.97,0.9133333333333334,0.9200725814533811,0.9009989259106906
 -1,-1,0.88,0.96,0.98,0.98,0.88,0.7773333333333333,0.40666666666666657,0.932,0.264,0.97,0.13599999999999998,0.9766666666666666,0.925,0.9338857017454859,0.9155441077441077
+-1,-1,0.8,0.94,0.96,0.98,0.8,0.7040000000000001,0.3733333333333333,0.8853333333333333,0.24399999999999994,0.932,0.132,0.97,0.8636666666666666,0.8822237320765974,0.8473146191282837

Information-Retrieval_evaluation_NanoSCIDOCS_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.44,0.8,0.82,0.84,0.44,0.09,0.4066666666666666,0.25166666666666665,0.324,0.3336666666666666,0.204,0.4186666666666667,0.615,0.4101274429849031,0.3292816325463611
 -1,-1,0.42,0.74,0.78,0.84,0.42,0.08866666666666667,0.37999999999999995,0.23566666666666664,0.308,0.31766666666666665,0.206,0.42266666666666663,0.5818571428571429,0.40435823767573387,0.323977515434263
 -1,-1,0.32,0.54,0.64,0.74,0.32,0.06666666666666667,0.26,0.16166666666666668,0.22800000000000004,0.2356666666666667,0.154,0.3156666666666667,0.44319047619047613,0.2935945171614566,0.2271492750494412
+-1,-1,0.44,0.7,0.76,0.82,0.44,0.09000000000000002,0.35999999999999993,0.22366666666666668,0.276,0.2856666666666667,0.18799999999999997,0.3856666666666666,0.5814126984126983,0.3770553629496287,0.29083941157524296

Information-Retrieval_evaluation_NanoSciFact_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.4,0.56,0.68,0.82,0.4,0.365,0.20666666666666667,0.54,0.156,0.67,0.092,0.81,0.5163809523809523,0.5786729320169597,0.5080130860531493
 -1,-1,0.44,0.62,0.68,0.76,0.44,0.405,0.23333333333333336,0.605,0.156,0.67,0.08599999999999998,0.75,0.5513809523809523,0.5979962793714768,0.5573177733530136
 -1,-1,0.54,0.72,0.82,0.86,0.54,0.505,0.26666666666666666,0.705,0.184,0.815,0.09799999999999998,0.86,0.6388333333333331,0.6928979313137813,0.6431673130790777
+-1,-1,0.54,0.62,0.68,0.78,0.54,0.505,0.22,0.605,0.14800000000000002,0.67,0.08799999999999997,0.77,0.6037142857142856,0.6369569682887986,0.5980723176336579

Information-Retrieval_evaluation_NanoTouche2020_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.5102040816326531,0.7959183673469388,0.8979591836734694,0.9183673469387755,0.5102040816326531,0.03854267866697781,0.4965986394557823,0.10902757502622276,0.4816326530612245,0.16598150420023525,0.3938775510204081,0.2628015390404495,0.6712585034013605,0.44267616813783334,0.3390085284860797
 -1,-1,0.5306122448979592,0.8571428571428571,0.8979591836734694,0.9795918367346939,0.5306122448979592,0.039526113999152644,0.5510204081632653,0.11537854933328684,0.5102040816326532,0.17364885334764324,0.40204081632653066,0.26913088576893424,0.7014415289925494,0.4579555008551029,0.34517137650160645
 -1,-1,0.5714285714285714,0.7346938775510204,0.8571428571428571,0.8979591836734694,0.5714285714285714,0.04160307096696755,0.48979591836734687,0.10938109580497314,0.46938775510204084,0.16462035443893633,0.40408163265306124,0.27764072821348407,0.6836977648202137,0.45369150936664365,0.34573275558813277
+-1,-1,0.6122448979591837,0.8163265306122449,0.9183673469387755,0.9795918367346939,0.6122448979591837,0.043687253263675355,0.5306122448979591,0.11567711645152232,0.48571428571428565,0.17379773177120716,0.42857142857142855,0.2854021806590398,0.7382896015549075,0.48361355760830715,0.3640696958602512

NanoBEIR_evaluation_mean_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.4730926216640503,0.665839874411303,0.7429199372056515,0.8167974882260598,0.4730926216640503,0.2725036155594467,0.29768707482993195,0.41722258489412517,0.23489481946624807,0.48364379561712173,0.1619905808477237,0.5647417533124149,0.5859600558171987,0.5146607033363005,0.43428965611088316
 -1,-1,0.4823547880690739,0.669010989010989,0.7413814756671899,0.8168916797488225,0.4823547880690739,0.27810226922930104,0.3059759288330717,0.4228096254762406,0.23863108320251178,0.49154870385803073,0.1618492935635793,0.5654237444317253,0.590928347163041,0.5201522210707754,0.44175014933476214
 -1,-1,0.5224175824175824,0.6872841444270017,0.7674725274725275,0.8383045525902669,0.5224175824175824,0.3112763025521349,0.3145996860282575,0.4609882318738122,0.24164521193092625,0.5276915472117948,0.1644678178963893,0.5956785393844413,0.6221403653036306,0.5535207015531378,0.47583411417450117
+-1,-1,0.4917111459968604,0.6658712715855573,0.7229513343799059,0.8076609105180533,0.4917111459968604,0.28480270100099275,0.2987650444793302,0.42648090438734276,0.22690109890109894,0.4814632766403525,0.16189010989010988,0.5712520445243282,0.5937206897410979,0.5244117853786112,0.4437624982006913

config.json

@@ -5,6 +5,7 @@
   "attention_probs_dropout_prob": 0.1,
   "classifier_dropout": null,
   "dtype": "float32",
+  "gradient_checkpointing": false,
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.1,
   "hidden_size": 384,
@@ -14,7 +15,7 @@
   "max_position_embeddings": 512,
   "model_type": "bert",
   "num_attention_heads": 12,
-  "num_hidden_layers": 12,
+  "num_hidden_layers": 6,
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
   "transformers_version": "4.57.3",

eval/Information-Retrieval_evaluation_NanoMSMARCO_results.csv

@@ -161,3 +161,16 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 3.5561877667140824,2500,0.32,0.56,0.62,0.72,0.32,0.32,0.18666666666666668,0.56,0.124,0.62,0.07200000000000001,0.72,0.4514126984126985,0.5164775067572812,0.46366130654724685
 3.9118065433854907,2750,0.32,0.56,0.62,0.74,0.32,0.32,0.18666666666666668,0.56,0.124,0.62,0.07400000000000001,0.74,0.45293650793650797,0.5218013262081452,0.4633491089409316
 4.2674253200568995,3000,0.32,0.56,0.62,0.74,0.32,0.32,0.18666666666666668,0.56,0.124,0.62,0.07400000000000001,0.74,0.4534126984126985,0.522258803283639,0.4638252994171221
+0,0,0.36,0.52,0.58,0.8,0.36,0.36,0.1733333333333333,0.52,0.11599999999999999,0.58,0.08,0.8,0.47960317460317464,0.5539831330912274,0.49062451473627944
+0.35561877667140823,250,0.34,0.52,0.56,0.74,0.34,0.34,0.1733333333333333,0.52,0.11200000000000002,0.56,0.07400000000000001,0.74,0.4500158730158729,0.5174080706686606,0.46196064893998323
+0.7112375533428165,500,0.32,0.5,0.56,0.72,0.32,0.32,0.16666666666666669,0.5,0.11200000000000002,0.56,0.07200000000000001,0.72,0.4341031746031746,0.5012733251987884,0.4486889042013871
+1.0668563300142249,750,0.34,0.5,0.6,0.72,0.34,0.34,0.16666666666666669,0.5,0.12,0.6,0.07200000000000001,0.72,0.45026984126984115,0.5139036260299831,0.46447330074346205
+1.422475106685633,1000,0.34,0.5,0.62,0.74,0.34,0.34,0.16666666666666669,0.5,0.124,0.62,0.07400000000000001,0.74,0.4536031746031746,0.5210510523549858,0.46670569936498585
+1.7780938833570412,1250,0.36,0.5,0.6,0.74,0.36,0.36,0.16666666666666669,0.5,0.12,0.6,0.07400000000000001,0.74,0.46438095238095234,0.5290463463305695,0.4767172276628289
+2.1337126600284497,1500,0.32,0.5,0.62,0.76,0.32,0.32,0.16666666666666669,0.5,0.124,0.62,0.07600000000000001,0.76,0.4488809523809524,0.5223690666255387,0.4601159696054782
+2.4893314366998576,1750,0.34,0.54,0.62,0.72,0.34,0.34,0.18,0.54,0.124,0.62,0.07200000000000001,0.72,0.45821428571428563,0.5209608161784584,0.4725671975002087
+2.844950213371266,2000,0.34,0.52,0.62,0.74,0.34,0.34,0.1733333333333333,0.52,0.124,0.62,0.07400000000000001,0.74,0.45904761904761904,0.5257041178737043,0.4716011553180688
+3.200568990042674,2250,0.32,0.54,0.62,0.72,0.32,0.32,0.18,0.54,0.124,0.62,0.07200000000000001,0.72,0.4467142857142856,0.5121749352237538,0.46142863144405133
+3.5561877667140824,2500,0.32,0.54,0.62,0.72,0.32,0.32,0.18,0.54,0.124,0.62,0.07200000000000001,0.72,0.4477142857142857,0.5130514102405308,0.4619196080152698
+3.9118065433854907,2750,0.32,0.54,0.6,0.72,0.32,0.32,0.18,0.54,0.12,0.6,0.07200000000000001,0.72,0.445095238095238,0.5106470686702358,0.4594786837773859
+4.2674253200568995,3000,0.32,0.54,0.62,0.72,0.32,0.32,0.18,0.54,0.124,0.62,0.07200000000000001,0.72,0.44588095238095227,0.5113600890173079,0.46015815095025

eval/Information-Retrieval_evaluation_NanoNQ_results.csv

@@ -161,3 +161,16 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 3.5561877667140824,2500,0.32,0.54,0.54,0.74,0.32,0.29,0.18666666666666665,0.52,0.11600000000000002,0.53,0.07800000000000001,0.71,0.4477936507936508,0.49985826827052954,0.43551003766964674
 3.9118065433854907,2750,0.32,0.54,0.54,0.74,0.32,0.29,0.18666666666666665,0.52,0.11600000000000002,0.53,0.07800000000000001,0.71,0.4477936507936508,0.49985826827052954,0.4354911744351764
 4.2674253200568995,3000,0.32,0.54,0.54,0.74,0.32,0.29,0.18666666666666665,0.52,0.11600000000000002,0.53,0.07800000000000001,0.71,0.44801587301587303,0.5000975716574514,0.435720694785091
+0,0,0.48,0.62,0.66,0.72,0.48,0.47,0.21333333333333332,0.6,0.14,0.64,0.07600000000000001,0.7,0.5643571428571428,0.5930818641709092,0.5653172420421086
+0.35561877667140823,250,0.42,0.56,0.62,0.64,0.42,0.4,0.2,0.56,0.136,0.61,0.07,0.63,0.5008333333333334,0.5317168989955815,0.511185095953843
+0.7112375533428165,500,0.4,0.54,0.58,0.62,0.4,0.38,0.19333333333333333,0.53,0.12400000000000003,0.56,0.068,0.61,0.4848571428571429,0.512054427234519,0.4915110884929105
+1.0668563300142249,750,0.38,0.54,0.58,0.62,0.38,0.36,0.19333333333333333,0.52,0.12400000000000003,0.56,0.068,0.61,0.4715238095238095,0.5015180678721897,0.47799298767512866
+1.422475106685633,1000,0.4,0.54,0.6,0.68,0.4,0.37,0.19333333333333333,0.52,0.128,0.58,0.07400000000000001,0.67,0.49257936507936506,0.5268400183767522,0.48764364970974095
+1.7780938833570412,1250,0.38,0.54,0.58,0.62,0.38,0.36,0.19333333333333333,0.52,0.12400000000000003,0.56,0.068,0.61,0.46485714285714286,0.49729388858372425,0.4736675596278874
+2.1337126600284497,1500,0.32,0.52,0.56,0.62,0.32,0.3,0.18666666666666665,0.5,0.12,0.54,0.068,0.61,0.4273333333333334,0.46876985232843404,0.43541647760436264
+2.4893314366998576,1750,0.38,0.54,0.58,0.62,0.38,0.37,0.19333333333333333,0.52,0.12400000000000003,0.56,0.068,0.61,0.4678333333333334,0.5013976208877609,0.4802464210451109
+2.844950213371266,2000,0.32,0.5,0.58,0.62,0.32,0.29,0.18,0.49,0.12400000000000003,0.56,0.068,0.61,0.4278888888888888,0.46610814242792437,0.43062060711217426
+3.200568990042674,2250,0.36,0.5,0.58,0.64,0.36,0.33,0.18,0.49,0.12400000000000003,0.56,0.07,0.63,0.4533888888888889,0.4894706080504006,0.4542179448441391
+3.5561877667140824,2500,0.36,0.52,0.58,0.62,0.36,0.33,0.18666666666666665,0.51,0.12400000000000003,0.56,0.068,0.61,0.4528333333333333,0.4848364769756531,0.45549754429982636
+3.9118065433854907,2750,0.36,0.52,0.58,0.62,0.36,0.33,0.18666666666666665,0.5,0.12400000000000003,0.56,0.068,0.61,0.45283333333333337,0.48430011761332376,0.4543847371198107
+4.2674253200568995,3000,0.34,0.5,0.58,0.62,0.34,0.31,0.18,0.49,0.12400000000000003,0.56,0.068,0.61,0.44116666666666665,0.47606860320855016,0.4435242837774235

eval/NanoBEIR_evaluation_mean_results.csv

@@ -161,3 +161,16 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 3.5561877667140824,2500,0.32,0.55,0.5800000000000001,0.73,0.32,0.305,0.18666666666666665,0.54,0.12000000000000001,0.575,0.07500000000000001,0.715,0.44960317460317467,0.5081678875139054,0.4495856721084468
 3.9118065433854907,2750,0.32,0.55,0.5800000000000001,0.74,0.32,0.305,0.18666666666666665,0.54,0.12000000000000001,0.575,0.07600000000000001,0.725,0.4503650793650794,0.5108297972393374,0.449420141688054
 4.2674253200568995,3000,0.32,0.55,0.5800000000000001,0.74,0.32,0.305,0.18666666666666665,0.54,0.12000000000000001,0.575,0.07600000000000001,0.725,0.45071428571428573,0.5111781874705452,0.4497729971011065
+0,0,0.42,0.5700000000000001,0.62,0.76,0.42,0.415,0.1933333333333333,0.56,0.128,0.61,0.07800000000000001,0.75,0.5219801587301587,0.5735324986310684,0.5279708783891941
+0.35561877667140823,250,0.38,0.54,0.5900000000000001,0.69,0.38,0.37,0.18666666666666665,0.54,0.12400000000000001,0.585,0.07200000000000001,0.685,0.4754246031746031,0.5245624848321211,0.4865728724469131
+0.7112375533428165,500,0.36,0.52,0.5700000000000001,0.6699999999999999,0.36,0.35,0.18,0.515,0.11800000000000002,0.56,0.07,0.665,0.45948015873015874,0.5066638762166538,0.4700999963471488
+1.0668563300142249,750,0.36,0.52,0.59,0.6699999999999999,0.36,0.35,0.18,0.51,0.12200000000000001,0.5800000000000001,0.07,0.665,0.4608968253968253,0.5077108469510864,0.47123314420929535
+1.422475106685633,1000,0.37,0.52,0.61,0.71,0.37,0.355,0.18,0.51,0.126,0.6,0.07400000000000001,0.7050000000000001,0.4730912698412698,0.5239455353658691,0.4771746745373634
+1.7780938833570412,1250,0.37,0.52,0.59,0.6799999999999999,0.37,0.36,0.18,0.51,0.12200000000000001,0.5800000000000001,0.07100000000000001,0.675,0.4646190476190476,0.5131701174571468,0.47519239364535815
+2.1337126600284497,1500,0.32,0.51,0.5900000000000001,0.69,0.32,0.31,0.17666666666666667,0.5,0.122,0.5800000000000001,0.07200000000000001,0.685,0.4381071428571429,0.4955694594769864,0.4477662236049204
+2.4893314366998576,1750,0.36,0.54,0.6,0.6699999999999999,0.36,0.355,0.18666666666666665,0.53,0.12400000000000001,0.5900000000000001,0.07,0.665,0.4630238095238095,0.5111792185331097,0.47640680927265977
+2.844950213371266,2000,0.33,0.51,0.6,0.6799999999999999,0.33,0.315,0.17666666666666664,0.505,0.12400000000000001,0.5900000000000001,0.07100000000000001,0.675,0.44346825396825396,0.4959061301508143,0.45111088121512155
+3.200568990042674,2250,0.33999999999999997,0.52,0.6,0.6799999999999999,0.33999999999999997,0.325,0.18,0.515,0.12400000000000001,0.5900000000000001,0.07100000000000001,0.675,0.45005158730158723,0.5008227716370772,0.45782328814409523
+3.5561877667140824,2500,0.33999999999999997,0.53,0.6,0.6699999999999999,0.33999999999999997,0.325,0.18333333333333332,0.525,0.12400000000000001,0.5900000000000001,0.07,0.665,0.45027380952380947,0.4989439436080919,0.4587085761575481
+3.9118065433854907,2750,0.33999999999999997,0.53,0.59,0.6699999999999999,0.33999999999999997,0.325,0.18333333333333332,0.52,0.12200000000000001,0.5800000000000001,0.07,0.665,0.4489642857142857,0.49747359314177975,0.45693171044859826
+4.2674253200568995,3000,0.33,0.52,0.6,0.6699999999999999,0.33,0.315,0.18,0.515,0.12400000000000001,0.5900000000000001,0.07,0.665,0.44352380952380943,0.493714346112929,0.45184121736383676

final_metrics.json

@@ -1,231 +1,231 @@
 {
   "nano_beir": {
     "NanoClimateFEVER_cosine_accuracy@1": 0.28,
-    "NanoClimateFEVER_cosine_accuracy@3": 0.4,
-    "NanoClimateFEVER_cosine_accuracy@5": 0.58,
-    "NanoClimateFEVER_cosine_accuracy@10": 0.68,
+    "NanoClimateFEVER_cosine_accuracy@3": 0.42,
+    "NanoClimateFEVER_cosine_accuracy@5": 0.5,
+    "NanoClimateFEVER_cosine_accuracy@10": 0.64,
     "NanoClimateFEVER_cosine_precision@1": 0.28,
-    "NanoClimateFEVER_cosine_precision@3": 0.14666666666666667,
-    "NanoClimateFEVER_cosine_precision@5": 0.132,
-    "NanoClimateFEVER_cosine_precision@10": 0.08399999999999999,
-    "NanoClimateFEVER_cosine_recall@1": 0.13499999999999998,
-    "NanoClimateFEVER_cosine_recall@3": 0.21,
-    "NanoClimateFEVER_cosine_recall@5": 0.294,
-    "NanoClimateFEVER_cosine_recall@10": 0.35200000000000004,
-    "NanoClimateFEVER_cosine_ndcg@10": 0.29076885639822775,
-    "NanoClimateFEVER_cosine_mrr@10": 0.38588095238095227,
-    "NanoClimateFEVER_cosine_map@100": 0.2284985743248978,
-    "NanoDBPedia_cosine_accuracy@1": 0.68,
-    "NanoDBPedia_cosine_accuracy@3": 0.84,
-    "NanoDBPedia_cosine_accuracy@5": 0.9,
-    "NanoDBPedia_cosine_accuracy@10": 0.96,
-    "NanoDBPedia_cosine_precision@1": 0.68,
-    "NanoDBPedia_cosine_precision@3": 0.5466666666666667,
-    "NanoDBPedia_cosine_precision@5": 0.452,
-    "NanoDBPedia_cosine_precision@10": 0.37200000000000005,
-    "NanoDBPedia_cosine_recall@1": 0.05716747444864907,
-    "NanoDBPedia_cosine_recall@3": 0.1337308951341992,
-    "NanoDBPedia_cosine_recall@5": 0.17566784068129068,
-    "NanoDBPedia_cosine_recall@10": 0.2632314620490831,
-    "NanoDBPedia_cosine_ndcg@10": 0.4849472222283775,
-    "NanoDBPedia_cosine_mrr@10": 0.7753333333333333,
-    "NanoDBPedia_cosine_map@100": 0.3229143949554386,
-    "NanoFEVER_cosine_accuracy@1": 0.82,
+    "NanoClimateFEVER_cosine_precision@3": 0.15333333333333332,
+    "NanoClimateFEVER_cosine_precision@5": 0.11600000000000002,
+    "NanoClimateFEVER_cosine_precision@10": 0.07400000000000001,
+    "NanoClimateFEVER_cosine_recall@1": 0.12666666666666665,
+    "NanoClimateFEVER_cosine_recall@3": 0.1973333333333333,
+    "NanoClimateFEVER_cosine_recall@5": 0.2606666666666666,
+    "NanoClimateFEVER_cosine_recall@10": 0.3123333333333333,
+    "NanoClimateFEVER_cosine_ndcg@10": 0.26290792445639205,
+    "NanoClimateFEVER_cosine_mrr@10": 0.37093650793650795,
+    "NanoClimateFEVER_cosine_map@100": 0.2087000001335581,
+    "NanoDBPedia_cosine_accuracy@1": 0.64,
+    "NanoDBPedia_cosine_accuracy@3": 0.82,
+    "NanoDBPedia_cosine_accuracy@5": 0.86,
+    "NanoDBPedia_cosine_accuracy@10": 0.9,
+    "NanoDBPedia_cosine_precision@1": 0.64,
+    "NanoDBPedia_cosine_precision@3": 0.4799999999999999,
+    "NanoDBPedia_cosine_precision@5": 0.4159999999999999,
+    "NanoDBPedia_cosine_precision@10": 0.366,
+    "NanoDBPedia_cosine_recall@1": 0.06869625936429839,
+    "NanoDBPedia_cosine_recall@3": 0.12411529604858355,
+    "NanoDBPedia_cosine_recall@5": 0.1649095059218987,
+    "NanoDBPedia_cosine_recall@10": 0.25973433711392624,
+    "NanoDBPedia_cosine_ndcg@10": 0.4696471920704787,
+    "NanoDBPedia_cosine_mrr@10": 0.7323809523809526,
+    "NanoDBPedia_cosine_map@100": 0.31155113021441067,
+    "NanoFEVER_cosine_accuracy@1": 0.8,
     "NanoFEVER_cosine_accuracy@3": 0.96,
-    "NanoFEVER_cosine_accuracy@5": 1.0,
-    "NanoFEVER_cosine_accuracy@10": 1.0,
-    "NanoFEVER_cosine_precision@1": 0.82,
-    "NanoFEVER_cosine_precision@3": 0.32,
-    "NanoFEVER_cosine_precision@5": 0.19999999999999996,
-    "NanoFEVER_cosine_precision@10": 0.102,
+    "NanoFEVER_cosine_accuracy@5": 0.96,
+    "NanoFEVER_cosine_accuracy@10": 0.98,
+    "NanoFEVER_cosine_precision@1": 0.8,
+    "NanoFEVER_cosine_precision@3": 0.32666666666666666,
+    "NanoFEVER_cosine_precision@5": 0.19599999999999995,
+    "NanoFEVER_cosine_precision@10": 0.09999999999999998,
     "NanoFEVER_cosine_recall@1": 0.7566666666666667,
-    "NanoFEVER_cosine_recall@3": 0.8966666666666667,
-    "NanoFEVER_cosine_recall@5": 0.9366666666666668,
-    "NanoFEVER_cosine_recall@10": 0.9466666666666668,
-    "NanoFEVER_cosine_ndcg@10": 0.8736355301798917,
-    "NanoFEVER_cosine_mrr@10": 0.8913333333333333,
-    "NanoFEVER_cosine_map@100": 0.8324328703703704,
-    "NanoFiQA2018_cosine_accuracy@1": 0.4,
-    "NanoFiQA2018_cosine_accuracy@3": 0.62,
-    "NanoFiQA2018_cosine_accuracy@5": 0.64,
-    "NanoFiQA2018_cosine_accuracy@10": 0.7,
-    "NanoFiQA2018_cosine_precision@1": 0.4,
-    "NanoFiQA2018_cosine_precision@3": 0.28,
-    "NanoFiQA2018_cosine_precision@5": 0.19199999999999995,
-    "NanoFiQA2018_cosine_precision@10": 0.11399999999999999,
-    "NanoFiQA2018_cosine_recall@1": 0.21941269841269842,
-    "NanoFiQA2018_cosine_recall@3": 0.4022142857142857,
-    "NanoFiQA2018_cosine_recall@5": 0.44707142857142856,
-    "NanoFiQA2018_cosine_recall@10": 0.509626984126984,
-    "NanoFiQA2018_cosine_ndcg@10": 0.4352400324035161,
-    "NanoFiQA2018_cosine_mrr@10": 0.505,
-    "NanoFiQA2018_cosine_map@100": 0.3798068762112574,
-    "NanoHotpotQA_cosine_accuracy@1": 0.8,
+    "NanoFEVER_cosine_recall@3": 0.9066666666666667,
+    "NanoFEVER_cosine_recall@5": 0.9066666666666667,
+    "NanoFEVER_cosine_recall@10": 0.9266666666666667,
+    "NanoFEVER_cosine_ndcg@10": 0.862302442184373,
+    "NanoFEVER_cosine_mrr@10": 0.8728571428571429,
+    "NanoFEVER_cosine_map@100": 0.827208000215349,
+    "NanoFiQA2018_cosine_accuracy@1": 0.38,
+    "NanoFiQA2018_cosine_accuracy@3": 0.48,
+    "NanoFiQA2018_cosine_accuracy@5": 0.56,
+    "NanoFiQA2018_cosine_accuracy@10": 0.62,
+    "NanoFiQA2018_cosine_precision@1": 0.38,
+    "NanoFiQA2018_cosine_precision@3": 0.19333333333333336,
+    "NanoFiQA2018_cosine_precision@5": 0.14,
+    "NanoFiQA2018_cosine_precision@10": 0.088,
+    "NanoFiQA2018_cosine_recall@1": 0.2072460317460318,
+    "NanoFiQA2018_cosine_recall@3": 0.3121031746031746,
+    "NanoFiQA2018_cosine_recall@5": 0.34743650793650793,
+    "NanoFiQA2018_cosine_recall@10": 0.4231031746031746,
+    "NanoFiQA2018_cosine_ndcg@10": 0.35669365584544394,
+    "NanoFiQA2018_cosine_mrr@10": 0.4389126984126985,
+    "NanoFiQA2018_cosine_map@100": 0.30271886425746414,
+    "NanoHotpotQA_cosine_accuracy@1": 0.72,
     "NanoHotpotQA_cosine_accuracy@3": 0.86,
-    "NanoHotpotQA_cosine_accuracy@5": 0.9,
+    "NanoHotpotQA_cosine_accuracy@5": 0.92,
     "NanoHotpotQA_cosine_accuracy@10": 0.92,
-    "NanoHotpotQA_cosine_precision@1": 0.8,
-    "NanoHotpotQA_cosine_precision@3": 0.4133333333333332,
-    "NanoHotpotQA_cosine_precision@5": 0.26799999999999996,
-    "NanoHotpotQA_cosine_precision@10": 0.13799999999999998,
-    "NanoHotpotQA_cosine_recall@1": 0.4,
-    "NanoHotpotQA_cosine_recall@3": 0.62,
-    "NanoHotpotQA_cosine_recall@5": 0.67,
-    "NanoHotpotQA_cosine_recall@10": 0.69,
-    "NanoHotpotQA_cosine_ndcg@10": 0.6846067758620142,
-    "NanoHotpotQA_cosine_mrr@10": 0.8385238095238097,
-    "NanoHotpotQA_cosine_map@100": 0.6229030032655473,
-    "NanoMSMARCO_cosine_accuracy@1": 0.44,
-    "NanoMSMARCO_cosine_accuracy@3": 0.7,
-    "NanoMSMARCO_cosine_accuracy@5": 0.72,
-    "NanoMSMARCO_cosine_accuracy@10": 0.84,
-    "NanoMSMARCO_cosine_precision@1": 0.44,
-    "NanoMSMARCO_cosine_precision@3": 0.2333333333333333,
-    "NanoMSMARCO_cosine_precision@5": 0.14400000000000002,
-    "NanoMSMARCO_cosine_precision@10": 0.084,
-    "NanoMSMARCO_cosine_recall@1": 0.44,
-    "NanoMSMARCO_cosine_recall@3": 0.7,
-    "NanoMSMARCO_cosine_recall@5": 0.72,
-    "NanoMSMARCO_cosine_recall@10": 0.84,
-    "NanoMSMARCO_cosine_ndcg@10": 0.6393050305464907,
-    "NanoMSMARCO_cosine_mrr@10": 0.5752380952380952,
-    "NanoMSMARCO_cosine_map@100": 0.5834313164313165,
-    "NanoNFCorpus_cosine_accuracy@1": 0.4,
-    "NanoNFCorpus_cosine_accuracy@3": 0.5,
-    "NanoNFCorpus_cosine_accuracy@5": 0.56,
-    "NanoNFCorpus_cosine_accuracy@10": 0.68,
-    "NanoNFCorpus_cosine_precision@1": 0.4,
-    "NanoNFCorpus_cosine_precision@3": 0.3466666666666666,
-    "NanoNFCorpus_cosine_precision@5": 0.32,
-    "NanoNFCorpus_cosine_precision@10": 0.282,
-    "NanoNFCorpus_cosine_recall@1": 0.017742022682771613,
-    "NanoNFCorpus_cosine_recall@3": 0.04218740437276733,
-    "NanoNFCorpus_cosine_recall@5": 0.061297156728343155,
-    "NanoNFCorpus_cosine_recall@10": 0.10232183760818475,
-    "NanoNFCorpus_cosine_ndcg@10": 0.3087896786838233,
-    "NanoNFCorpus_cosine_mrr@10": 0.46851587301587294,
-    "NanoNFCorpus_cosine_map@100": 0.12702712283624432,
-    "NanoNQ_cosine_accuracy@1": 0.44,
-    "NanoNQ_cosine_accuracy@3": 0.58,
-    "NanoNQ_cosine_accuracy@5": 0.64,
+    "NanoHotpotQA_cosine_precision@1": 0.72,
+    "NanoHotpotQA_cosine_precision@3": 0.38666666666666666,
+    "NanoHotpotQA_cosine_precision@5": 0.272,
+    "NanoHotpotQA_cosine_precision@10": 0.144,
+    "NanoHotpotQA_cosine_recall@1": 0.36,
+    "NanoHotpotQA_cosine_recall@3": 0.58,
+    "NanoHotpotQA_cosine_recall@5": 0.68,
+    "NanoHotpotQA_cosine_recall@10": 0.72,
+    "NanoHotpotQA_cosine_ndcg@10": 0.6741831390182679,
+    "NanoHotpotQA_cosine_mrr@10": 0.7986666666666666,
+    "NanoHotpotQA_cosine_map@100": 0.5983102633770884,
+    "NanoMSMARCO_cosine_accuracy@1": 0.32,
+    "NanoMSMARCO_cosine_accuracy@3": 0.56,
+    "NanoMSMARCO_cosine_accuracy@5": 0.62,
+    "NanoMSMARCO_cosine_accuracy@10": 0.74,
+    "NanoMSMARCO_cosine_precision@1": 0.32,
+    "NanoMSMARCO_cosine_precision@3": 0.18666666666666668,
+    "NanoMSMARCO_cosine_precision@5": 0.124,
+    "NanoMSMARCO_cosine_precision@10": 0.07400000000000001,
+    "NanoMSMARCO_cosine_recall@1": 0.32,
+    "NanoMSMARCO_cosine_recall@3": 0.56,
+    "NanoMSMARCO_cosine_recall@5": 0.62,
+    "NanoMSMARCO_cosine_recall@10": 0.74,
+    "NanoMSMARCO_cosine_ndcg@10": 0.522258803283639,
+    "NanoMSMARCO_cosine_mrr@10": 0.4534126984126985,
+    "NanoMSMARCO_cosine_map@100": 0.4638252994171221,
+    "NanoNFCorpus_cosine_accuracy@1": 0.34,
+    "NanoNFCorpus_cosine_accuracy@3": 0.48,
+    "NanoNFCorpus_cosine_accuracy@5": 0.5,
+    "NanoNFCorpus_cosine_accuracy@10": 0.58,
+    "NanoNFCorpus_cosine_precision@1": 0.34,
+    "NanoNFCorpus_cosine_precision@3": 0.33333333333333326,
+    "NanoNFCorpus_cosine_precision@5": 0.292,
+    "NanoNFCorpus_cosine_precision@10": 0.262,
+    "NanoNFCorpus_cosine_recall@1": 0.03047223530556736,
+    "NanoNFCorpus_cosine_recall@3": 0.0543561699321758,
+    "NanoNFCorpus_cosine_recall@5": 0.06787885069496813,
+    "NanoNFCorpus_cosine_recall@10": 0.10337021977345857,
+    "NanoNFCorpus_cosine_ndcg@10": 0.2963492902849603,
+    "NanoNFCorpus_cosine_mrr@10": 0.4257142857142857,
+    "NanoNFCorpus_cosine_map@100": 0.12099779665938908,
+    "NanoNQ_cosine_accuracy@1": 0.32,
+    "NanoNQ_cosine_accuracy@3": 0.54,
+    "NanoNQ_cosine_accuracy@5": 0.54,
     "NanoNQ_cosine_accuracy@10": 0.74,
-    "NanoNQ_cosine_precision@1": 0.44,
-    "NanoNQ_cosine_precision@3": 0.20666666666666664,
-    "NanoNQ_cosine_precision@5": 0.14,
-    "NanoNQ_cosine_precision@10": 0.08,
-    "NanoNQ_cosine_recall@1": 0.41,
-    "NanoNQ_cosine_recall@3": 0.56,
-    "NanoNQ_cosine_recall@5": 0.63,
+    "NanoNQ_cosine_precision@1": 0.32,
+    "NanoNQ_cosine_precision@3": 0.18666666666666665,
+    "NanoNQ_cosine_precision@5": 0.11600000000000002,
+    "NanoNQ_cosine_precision@10": 0.07800000000000001,
+    "NanoNQ_cosine_recall@1": 0.29,
+    "NanoNQ_cosine_recall@3": 0.52,
+    "NanoNQ_cosine_recall@5": 0.53,
     "NanoNQ_cosine_recall@10": 0.71,
-    "NanoNQ_cosine_ndcg@10": 0.5669662624959938,
-    "NanoNQ_cosine_mrr@10": 0.5335555555555557,
-    "NanoNQ_cosine_map@100": 0.5268891955660058,
-    "NanoQuoraRetrieval_cosine_accuracy@1": 0.88,
-    "NanoQuoraRetrieval_cosine_accuracy@3": 0.96,
-    "NanoQuoraRetrieval_cosine_accuracy@5": 0.98,
+    "NanoNQ_cosine_ndcg@10": 0.49985826827052954,
+    "NanoNQ_cosine_mrr@10": 0.4477936507936508,
+    "NanoNQ_cosine_map@100": 0.4354984725628689,
+    "NanoQuoraRetrieval_cosine_accuracy@1": 0.8,
+    "NanoQuoraRetrieval_cosine_accuracy@3": 0.94,
+    "NanoQuoraRetrieval_cosine_accuracy@5": 0.96,
     "NanoQuoraRetrieval_cosine_accuracy@10": 0.98,
-    "NanoQuoraRetrieval_cosine_precision@1": 0.88,
-    "NanoQuoraRetrieval_cosine_precision@3": 0.40666666666666657,
-    "NanoQuoraRetrieval_cosine_precision@5": 0.264,
-    "NanoQuoraRetrieval_cosine_precision@10": 0.13599999999999998,
-    "NanoQuoraRetrieval_cosine_recall@1": 0.7773333333333333,
-    "NanoQuoraRetrieval_cosine_recall@3": 0.932,
-    "NanoQuoraRetrieval_cosine_recall@5": 0.97,
-    "NanoQuoraRetrieval_cosine_recall@10": 0.9766666666666666,
-    "NanoQuoraRetrieval_cosine_ndcg@10": 0.9338857017454859,
-    "NanoQuoraRetrieval_cosine_mrr@10": 0.925,
-    "NanoQuoraRetrieval_cosine_map@100": 0.9155441077441077,
-    "NanoSCIDOCS_cosine_accuracy@1": 0.32,
-    "NanoSCIDOCS_cosine_accuracy@3": 0.54,
-    "NanoSCIDOCS_cosine_accuracy@5": 0.64,
-    "NanoSCIDOCS_cosine_accuracy@10": 0.74,
-    "NanoSCIDOCS_cosine_precision@1": 0.32,
-    "NanoSCIDOCS_cosine_precision@3": 0.26,
-    "NanoSCIDOCS_cosine_precision@5": 0.22800000000000004,
-    "NanoSCIDOCS_cosine_precision@10": 0.154,
-    "NanoSCIDOCS_cosine_recall@1": 0.06666666666666667,
-    "NanoSCIDOCS_cosine_recall@3": 0.16166666666666668,
-    "NanoSCIDOCS_cosine_recall@5": 0.2356666666666667,
-    "NanoSCIDOCS_cosine_recall@10": 0.3156666666666667,
-    "NanoSCIDOCS_cosine_ndcg@10": 0.2935945171614566,
-    "NanoSCIDOCS_cosine_mrr@10": 0.44319047619047613,
-    "NanoSCIDOCS_cosine_map@100": 0.2271492750494412,
-    "NanoArguAna_cosine_accuracy@1": 0.22,
-    "NanoArguAna_cosine_accuracy@3": 0.52,
-    "NanoArguAna_cosine_accuracy@5": 0.74,
-    "NanoArguAna_cosine_accuracy@10": 0.9,
-    "NanoArguAna_cosine_precision@1": 0.22,
-    "NanoArguAna_cosine_precision@3": 0.17333333333333337,
-    "NanoArguAna_cosine_precision@5": 0.14800000000000002,
-    "NanoArguAna_cosine_precision@10": 0.08999999999999998,
-    "NanoArguAna_cosine_recall@1": 0.22,
-    "NanoArguAna_cosine_recall@3": 0.52,
-    "NanoArguAna_cosine_recall@5": 0.74,
-    "NanoArguAna_cosine_recall@10": 0.9,
-    "NanoArguAna_cosine_ndcg@10": 0.5374400718050902,
-    "NanoArguAna_cosine_mrr@10": 0.4237222222222221,
-    "NanoArguAna_cosine_map@100": 0.4303466788466788,
+    "NanoQuoraRetrieval_cosine_precision@1": 0.8,
+    "NanoQuoraRetrieval_cosine_precision@3": 0.3733333333333333,
+    "NanoQuoraRetrieval_cosine_precision@5": 0.24399999999999994,
+    "NanoQuoraRetrieval_cosine_precision@10": 0.132,
+    "NanoQuoraRetrieval_cosine_recall@1": 0.7040000000000001,
+    "NanoQuoraRetrieval_cosine_recall@3": 0.8853333333333333,
+    "NanoQuoraRetrieval_cosine_recall@5": 0.932,
+    "NanoQuoraRetrieval_cosine_recall@10": 0.97,
+    "NanoQuoraRetrieval_cosine_ndcg@10": 0.8822237320765974,
+    "NanoQuoraRetrieval_cosine_mrr@10": 0.8636666666666666,
+    "NanoQuoraRetrieval_cosine_map@100": 0.8473146191282837,
+    "NanoSCIDOCS_cosine_accuracy@1": 0.44,
+    "NanoSCIDOCS_cosine_accuracy@3": 0.7,
+    "NanoSCIDOCS_cosine_accuracy@5": 0.76,
+    "NanoSCIDOCS_cosine_accuracy@10": 0.82,
+    "NanoSCIDOCS_cosine_precision@1": 0.44,
+    "NanoSCIDOCS_cosine_precision@3": 0.35999999999999993,
+    "NanoSCIDOCS_cosine_precision@5": 0.276,
+    "NanoSCIDOCS_cosine_precision@10": 0.18799999999999997,
+    "NanoSCIDOCS_cosine_recall@1": 0.09000000000000002,
+    "NanoSCIDOCS_cosine_recall@3": 0.22366666666666668,
+    "NanoSCIDOCS_cosine_recall@5": 0.2856666666666667,
+    "NanoSCIDOCS_cosine_recall@10": 0.3856666666666666,
+    "NanoSCIDOCS_cosine_ndcg@10": 0.3770553629496287,
+    "NanoSCIDOCS_cosine_mrr@10": 0.5814126984126983,
+    "NanoSCIDOCS_cosine_map@100": 0.29083941157524296,
+    "NanoArguAna_cosine_accuracy@1": 0.2,
+    "NanoArguAna_cosine_accuracy@3": 0.46,
+    "NanoArguAna_cosine_accuracy@5": 0.62,
+    "NanoArguAna_cosine_accuracy@10": 0.82,
+    "NanoArguAna_cosine_precision@1": 0.2,
+    "NanoArguAna_cosine_precision@3": 0.1533333333333333,
+    "NanoArguAna_cosine_precision@5": 0.124,
+    "NanoArguAna_cosine_precision@10": 0.08199999999999999,
+    "NanoArguAna_cosine_recall@1": 0.2,
+    "NanoArguAna_cosine_recall@3": 0.46,
+    "NanoArguAna_cosine_recall@5": 0.62,
+    "NanoArguAna_cosine_recall@10": 0.82,
+    "NanoArguAna_cosine_ndcg@10": 0.4933028735845294,
+    "NanoArguAna_cosine_mrr@10": 0.390611111111111,
+    "NanoArguAna_cosine_map@100": 0.3998066055743007,
     "NanoSciFact_cosine_accuracy@1": 0.54,
-    "NanoSciFact_cosine_accuracy@3": 0.72,
-    "NanoSciFact_cosine_accuracy@5": 0.82,
-    "NanoSciFact_cosine_accuracy@10": 0.86,
+    "NanoSciFact_cosine_accuracy@3": 0.62,
+    "NanoSciFact_cosine_accuracy@5": 0.68,
+    "NanoSciFact_cosine_accuracy@10": 0.78,
     "NanoSciFact_cosine_precision@1": 0.54,
-    "NanoSciFact_cosine_precision@3": 0.26666666666666666,
-    "NanoSciFact_cosine_precision@5": 0.184,
-    "NanoSciFact_cosine_precision@10": 0.09799999999999998,
+    "NanoSciFact_cosine_precision@3": 0.22,
+    "NanoSciFact_cosine_precision@5": 0.14800000000000002,
+    "NanoSciFact_cosine_precision@10": 0.08799999999999997,
     "NanoSciFact_cosine_recall@1": 0.505,
-    "NanoSciFact_cosine_recall@3": 0.705,
-    "NanoSciFact_cosine_recall@5": 0.815,
-    "NanoSciFact_cosine_recall@10": 0.86,
-    "NanoSciFact_cosine_ndcg@10": 0.6928979313137813,
-    "NanoSciFact_cosine_mrr@10": 0.6388333333333331,
-    "NanoSciFact_cosine_map@100": 0.6431673130790777,
-    "NanoTouche2020_cosine_accuracy@1": 0.5714285714285714,
-    "NanoTouche2020_cosine_accuracy@3": 0.7346938775510204,
-    "NanoTouche2020_cosine_accuracy@5": 0.8571428571428571,
-    "NanoTouche2020_cosine_accuracy@10": 0.8979591836734694,
-    "NanoTouche2020_cosine_precision@1": 0.5714285714285714,
-    "NanoTouche2020_cosine_precision@3": 0.48979591836734687,
-    "NanoTouche2020_cosine_precision@5": 0.46938775510204084,
-    "NanoTouche2020_cosine_precision@10": 0.40408163265306124,
-    "NanoTouche2020_cosine_recall@1": 0.04160307096696755,
-    "NanoTouche2020_cosine_recall@3": 0.10938109580497314,
-    "NanoTouche2020_cosine_recall@5": 0.16462035443893633,
-    "NanoTouche2020_cosine_recall@10": 0.27764072821348407,
-    "NanoTouche2020_cosine_ndcg@10": 0.45369150936664365,
-    "NanoTouche2020_cosine_mrr@10": 0.6836977648202137,
-    "NanoTouche2020_cosine_map@100": 0.34573275558813277,
-    "NanoBEIR_mean_cosine_accuracy@1": 0.5224175824175824,
-    "NanoBEIR_mean_cosine_accuracy@3": 0.6872841444270017,
-    "NanoBEIR_mean_cosine_accuracy@5": 0.7674725274725275,
-    "NanoBEIR_mean_cosine_accuracy@10": 0.8383045525902669,
-    "NanoBEIR_mean_cosine_precision@1": 0.5224175824175824,
-    "NanoBEIR_mean_cosine_precision@3": 0.3145996860282575,
-    "NanoBEIR_mean_cosine_precision@5": 0.24164521193092625,
-    "NanoBEIR_mean_cosine_precision@10": 0.1644678178963893,
-    "NanoBEIR_mean_cosine_recall@1": 0.3112763025521349,
-    "NanoBEIR_mean_cosine_recall@3": 0.4609882318738122,
-    "NanoBEIR_mean_cosine_recall@5": 0.5276915472117948,
-    "NanoBEIR_mean_cosine_recall@10": 0.5956785393844413,
-    "NanoBEIR_mean_cosine_ndcg@10": 0.5535207015531378,
-    "NanoBEIR_mean_cosine_mrr@10": 0.6221403653036306,
-    "NanoBEIR_mean_cosine_map@100": 0.47583411417450117
+    "NanoSciFact_cosine_recall@3": 0.605,
+    "NanoSciFact_cosine_recall@5": 0.67,
+    "NanoSciFact_cosine_recall@10": 0.77,
+    "NanoSciFact_cosine_ndcg@10": 0.6369569682887986,
+    "NanoSciFact_cosine_mrr@10": 0.6037142857142856,
+    "NanoSciFact_cosine_map@100": 0.5980723176336579,
+    "NanoTouche2020_cosine_accuracy@1": 0.6122448979591837,
+    "NanoTouche2020_cosine_accuracy@3": 0.8163265306122449,
+    "NanoTouche2020_cosine_accuracy@5": 0.9183673469387755,
+    "NanoTouche2020_cosine_accuracy@10": 0.9795918367346939,
+    "NanoTouche2020_cosine_precision@1": 0.6122448979591837,
+    "NanoTouche2020_cosine_precision@3": 0.5306122448979591,
+    "NanoTouche2020_cosine_precision@5": 0.48571428571428565,
+    "NanoTouche2020_cosine_precision@10": 0.42857142857142855,
+    "NanoTouche2020_cosine_recall@1": 0.043687253263675355,
+    "NanoTouche2020_cosine_recall@3": 0.11567711645152232,
+    "NanoTouche2020_cosine_recall@5": 0.17379773177120716,
+    "NanoTouche2020_cosine_recall@10": 0.2854021806590398,
+    "NanoTouche2020_cosine_ndcg@10": 0.48361355760830715,
+    "NanoTouche2020_cosine_mrr@10": 0.7382896015549075,
+    "NanoTouche2020_cosine_map@100": 0.3640696958602512,
+    "NanoBEIR_mean_cosine_accuracy@1": 0.4917111459968604,
+    "NanoBEIR_mean_cosine_accuracy@3": 0.6658712715855573,
+    "NanoBEIR_mean_cosine_accuracy@5": 0.7229513343799059,
+    "NanoBEIR_mean_cosine_accuracy@10": 0.8076609105180533,
+    "NanoBEIR_mean_cosine_precision@1": 0.4917111459968604,
+    "NanoBEIR_mean_cosine_precision@3": 0.2987650444793302,
+    "NanoBEIR_mean_cosine_precision@5": 0.22690109890109894,
+    "NanoBEIR_mean_cosine_precision@10": 0.16189010989010988,
+    "NanoBEIR_mean_cosine_recall@1": 0.28480270100099275,
+    "NanoBEIR_mean_cosine_recall@3": 0.42648090438734276,
+    "NanoBEIR_mean_cosine_recall@5": 0.4814632766403525,
+    "NanoBEIR_mean_cosine_recall@10": 0.5712520445243282,
+    "NanoBEIR_mean_cosine_ndcg@10": 0.5244117853786112,
+    "NanoBEIR_mean_cosine_mrr@10": 0.5937206897410979,
+    "NanoBEIR_mean_cosine_map@100": 0.4437624982006913
   },
   "beir_touche2020": {
-    "BeIR-touche2020-subset-test_cosine_accuracy@1": 0.7346938775510204,
+    "BeIR-touche2020-subset-test_cosine_accuracy@1": 0.8571428571428571,
     "BeIR-touche2020-subset-test_cosine_accuracy@3": 0.9795918367346939,
     "BeIR-touche2020-subset-test_cosine_accuracy@5": 1.0,
     "BeIR-touche2020-subset-test_cosine_accuracy@10": 1.0,
-    "BeIR-touche2020-subset-test_cosine_precision@1": 0.7346938775510204,
-    "BeIR-touche2020-subset-test_cosine_precision@3": 0.727891156462585,
-    "BeIR-touche2020-subset-test_cosine_precision@5": 0.7183673469387756,
-    "BeIR-touche2020-subset-test_cosine_precision@10": 0.6326530612244898,
-    "BeIR-touche2020-subset-test_cosine_recall@1": 0.01638254490984421,
-    "BeIR-touche2020-subset-test_cosine_recall@3": 0.048596148261189916,
-    "BeIR-touche2020-subset-test_cosine_recall@5": 0.07960185791379523,
-    "BeIR-touche2020-subset-test_cosine_recall@10": 0.1400201362033687,
-    "BeIR-touche2020-subset-test_cosine_ndcg@10": 0.6620487941595593,
-    "BeIR-touche2020-subset-test_cosine_mrr@10": 0.8476190476190478,
-    "BeIR-touche2020-subset-test_cosine_map@100": 0.30295778120799477
+    "BeIR-touche2020-subset-test_cosine_precision@1": 0.8571428571428571,
+    "BeIR-touche2020-subset-test_cosine_precision@3": 0.802721088435374,
+    "BeIR-touche2020-subset-test_cosine_precision@5": 0.7387755102040815,
+    "BeIR-touche2020-subset-test_cosine_precision@10": 0.6571428571428573,
+    "BeIR-touche2020-subset-test_cosine_recall@1": 0.01898438501321,
+    "BeIR-touche2020-subset-test_cosine_recall@3": 0.05323720714947885,
+    "BeIR-touche2020-subset-test_cosine_recall@5": 0.0818345425971837,
+    "BeIR-touche2020-subset-test_cosine_recall@10": 0.14545490934511227,
+    "BeIR-touche2020-subset-test_cosine_ndcg@10": 0.7018027446625917,
+    "BeIR-touche2020-subset-test_cosine_mrr@10": 0.9200680272108844,
+    "BeIR-touche2020-subset-test_cosine_map@100": 0.30282137720059765
   }
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c87b8b69288407a0c0812ffcf8f512e8a357c6167ee55e9b40c8a92ca30ab4ed
-size 133462128
+oid sha256:0af2eedea8f246b94f5ad89cf972791b4ddb4c7f0b89f7a0df2cdf130a0bcb34
+size 90864192

tokenizer_config.json

@@ -41,14 +41,14 @@
       "special": true
     }
   },
-  "clean_up_tokenization_spaces": true,
+  "clean_up_tokenization_spaces": false,
   "cls_token": "[CLS]",
   "do_basic_tokenize": true,
   "do_lower_case": true,
   "extra_special_tokens": {},
   "mask_token": "[MASK]",
   "max_length": 128,
-  "model_max_length": 512,
+  "model_max_length": 256,
   "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 sha256:69add64e78381e4e91d8ed5dbbfac6dae3751304e4d80b9d6076dcda35b01192
+oid sha256:499f0311b0ac3b392c2e2491b9715577395a62eaae22effc1f3e4c947639698d
 size 6161