Add OAI new models

results.py

@@ -99,6 +99,8 @@ MODELS = [
     "st-polish-paraphrase-from-mpnet",
     "text2vec-base-chinese",
     "text2vec-large-chinese",
+    "text-embedding-3-large",
+    "text-embedding-3-small",
     "text-embedding-ada-002",
     "text-similarity-ada-001",
     "text-similarity-babbage-001",

results/text-embedding-3-large/AmazonCounterfactualClassification.json

@@ -0,0 +1 @@
+{"test": {"en": {"accuracy": 0.7892537313}}, "mteb_dataset_name": "AmazonCounterfactualClassification"}

results/text-embedding-3-large/AmazonPolarityClassification.json

@@ -0,0 +1 @@
+{"test": {"accuracy": 0.9284965}, "mteb_dataset_name": "AmazonPolarityClassification"}

results/text-embedding-3-large/AmazonReviewsClassification.json

@@ -0,0 +1 @@
+{"test": {"en": {"accuracy": 0.48698}}, "mteb_dataset_name": "AmazonReviewsClassification"}

results/text-embedding-3-large/ArguAna.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.58046}, "mteb_dataset_name": "ArguAna"}

results/text-embedding-3-large/ArxivClusteringP2P.json

@@ -0,0 +1 @@
+{"test": {"v_measure": 0.49014258}, "mteb_dataset_name": "ArxivClusteringP2P"}

results/text-embedding-3-large/ArxivClusteringS2S.json

@@ -0,0 +1 @@
+{"test": {"v_measure": 0.4445153329}, "mteb_dataset_name": "ArxivClusteringS2S"}

results/text-embedding-3-large/AskUbuntuDupQuestions.json

@@ -0,0 +1 @@
+{"test": {"map": 0.6502685441}, "mteb_dataset_name": "AskUbuntuDupQuestions"}

results/text-embedding-3-large/BIOSSES.json

@@ -0,0 +1 @@
+{"test": {"cos_sim": {"spearman": 0.8468265244}}, "mteb_dataset_name": "BIOSSES"}

results/text-embedding-3-large/Banking77Classification.json

@@ -0,0 +1 @@
+{"test": {"accuracy": 0.8568831169}, "mteb_dataset_name": "Banking77Classification"}

results/text-embedding-3-large/BiorxivClusteringP2P.json

@@ -0,0 +1 @@
+{"test": {"v_measure": 0.3803191997}, "mteb_dataset_name": "BiorxivClusteringP2P"}

results/text-embedding-3-large/BiorxivClusteringS2S.json

@@ -0,0 +1 @@
+{"test": {"v_measure": 0.365267055}, "mteb_dataset_name": "BiorxivClusteringS2S"}

results/text-embedding-3-large/CQADupstackAndroidRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.57278}, "mteb_dataset_name": "CQADupstackAndroidRetrieval"}

results/text-embedding-3-large/CQADupstackEnglishRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.55772}, "mteb_dataset_name": "CQADupstackEnglishRetrieval"}

results/text-embedding-3-large/CQADupstackGamingRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.65401}, "mteb_dataset_name": "CQADupstackGamingRetrieval"}

results/text-embedding-3-large/CQADupstackGisRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.45633}, "mteb_dataset_name": "CQADupstackGisRetrieval"}

results/text-embedding-3-large/CQADupstackMathematicaRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.36994}, "mteb_dataset_name": "CQADupstackMathematicaRetrieval"}

results/text-embedding-3-large/CQADupstackPhysicsRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.52162}, "mteb_dataset_name": "CQADupstackPhysicsRetrieval"}

results/text-embedding-3-large/CQADupstackProgrammersRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.49094}, "mteb_dataset_name": "CQADupstackProgrammersRetrieval"}

results/text-embedding-3-large/CQADupstackRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.4753733333}, "mteb_dataset_name": "CQADupstackRetrieval"}

results/text-embedding-3-large/CQADupstackStatsRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.40672}, "mteb_dataset_name": "CQADupstackStatsRetrieval"}

results/text-embedding-3-large/CQADupstackTexRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.3456}, "mteb_dataset_name": "CQADupstackTexRetrieval"}

results/text-embedding-3-large/CQADupstackUnixRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.50024}, "mteb_dataset_name": "CQADupstackUnixRetrieval"}

results/text-embedding-3-large/CQADupstackWebmastersRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.45285}, "mteb_dataset_name": "CQADupstackWebmastersRetrieval"}

results/text-embedding-3-large/CQADupstackWordpressRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.37573}, "mteb_dataset_name": "CQADupstackWordpressRetrieval"}

results/text-embedding-3-large/ClimateFEVER.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.30275}, "mteb_dataset_name": "ClimateFEVER"}

results/text-embedding-3-large/DBPedia.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.44755}, "mteb_dataset_name": "DBPedia"}

results/text-embedding-3-large/EmotionClassification.json

@@ -0,0 +1 @@
+{"test": {"accuracy": 0.51585}, "mteb_dataset_name": "EmotionClassification"}

results/text-embedding-3-large/FEVER.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.87937}, "mteb_dataset_name": "FEVER"}

results/text-embedding-3-large/FiQA2018.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.55002}, "mteb_dataset_name": "FiQA2018"}

results/text-embedding-3-large/HotpotQA.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.71578}, "mteb_dataset_name": "HotpotQA"}

results/text-embedding-3-large/ImdbClassification.json

@@ -0,0 +1 @@
+{"test": {"accuracy": 0.876704}, "mteb_dataset_name": "ImdbClassification"}

results/text-embedding-3-large/MSMARCO.json

@@ -0,0 +1 @@
+{"dev": {"ndcg_at_10": 0.40245}, "mteb_dataset_name": "MSMARCO"}

results/text-embedding-3-large/MTOPDomainClassification.json

@@ -0,0 +1 @@
+{"test": {"en": {"accuracy": 0.953625171}}, "mteb_dataset_name": "MTOPDomainClassification"}

results/text-embedding-3-large/MTOPIntentClassification.json

@@ -0,0 +1 @@
+{"test": {"en": {"v_measure": 0.7506839945}}, "mteb_dataset_name": "MTOPIntentClassification"}

results/text-embedding-3-large/MassiveIntentClassification.json

@@ -0,0 +1 @@
+{"test": {"en": {"accuracy": 0.7463685272}}, "mteb_dataset_name": "MassiveIntentClassification"}

results/text-embedding-3-large/MassiveScenarioClassification.json

@@ -0,0 +1 @@
+{"test": {"en": {"accuracy": 0.7979152656}}, "mteb_dataset_name": "MassiveScenarioClassification"}

results/text-embedding-3-large/MedrxivClusteringP2P.json

@@ -0,0 +1 @@
+{"test": {"v_measure": 0.3270498448}, "mteb_dataset_name": "MedrxivClusteringP2P"}

results/text-embedding-3-large/MedrxivClusteringS2S.json

@@ -0,0 +1 @@
+{"test": {"v_measure": 0.3126859693}, "mteb_dataset_name": "MedrxivClusteringS2S"}

results/text-embedding-3-large/MindSmallReranking.json

@@ -0,0 +1 @@
+{"test": {"map": 0.298643072}, "mteb_dataset_name": "MindSmallReranking"}

results/text-embedding-3-large/NFCorpus.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.42071}, "mteb_dataset_name": "NFCorpus"}

results/text-embedding-3-large/NQ.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.61273}, "mteb_dataset_name": "NQ"}

results/text-embedding-3-large/QuoraRetrieval.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.89051}, "mteb_dataset_name": "QuoraRetrieval"}

results/text-embedding-3-large/RedditClustering.json

@@ -0,0 +1 @@
+{"test": {"v_measure": 0.6783736931}, "mteb_dataset_name": "RedditClustering"}

results/text-embedding-3-large/RedditClusteringP2P.json

@@ -0,0 +1 @@
+{"test": {"v_measure": 0.6796206292}, "mteb_dataset_name": "RedditClusteringP2P"}

results/text-embedding-3-large/SCIDOCS.json

@@ -0,0 +1 @@
+{"test": {"ndcg_at_10": 0.23114}, "mteb_dataset_name": "SCIDOCS"}

results/text-embedding-3-large/SICK-R.json

@@ -0,0 +1 @@
+{"test": {"cos_sim": {"spearman": 0.7900399379}}, "mteb_dataset_name": "SICK-R"}

results/text-embedding-3-large/STS12.json

@@ -0,0 +1 @@
+{"test": {"cos_sim": {"spearman": 0.7283588741}}, "mteb_dataset_name": "STS12"}

results/text-embedding-3-large/STS13.json

@@ -0,0 +1 @@
+{"test": {"cos_sim": {"spearman": 0.8609681753}}, "mteb_dataset_name": "STS13"}