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"results/sentence-transformers__sentence-t5-large/no_revision_available/MasakhaNEWSClusteringS2S.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/BUCC.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/ArxivClusteringP2P.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/TwitterURLCorpus.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/STS22.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/AmazonReviewsClassification.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/CQADupstackGamingRetrieval.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/NFCorpus.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/STS15.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/AmazonPolarityClassification.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/MTOPIntentClassification.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/HALClusteringS2S.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/STS13.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/SummEval.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/ClimateFEVER.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/MasakhaNEWSClassification.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/CQADupstackStatsRetrieval.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/TwitterSemEval2015.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/CQADupstackWebmastersRetrieval.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/MedrxivClusteringP2P.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/TwentyNewsgroupsClustering.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/TenKGnadClusteringP2P.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/FEVER.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/OpusparcusPC.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/MSMARCO.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/MTOPDomainClassification.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/QuoraRetrieval.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/BlurbsClusteringS2S.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/SICKFr.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/STS12.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/AmazonCounterfactualClassification.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/CQADupstackMathematicaRetrieval.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/PawsXPairClassification.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/StackExchangeClusteringP2P.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/CQADupstackPhysicsRetrieval.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/CQADupstackWordpressRetrieval.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/XPQARetrieval.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/STSBenchmarkMultilingualSTS.json", + "results/sentence-transformers__sentence-t5-large/no_revision_available/StackOverflowDupQuestions.json" + ], + "intfloat__e5-large": [ + "results/intfloat__e5-large/no_revision_available/MassiveIntentClassification.json", + "results/intfloat__e5-large/no_revision_available/SweRecClassification.json", + "results/intfloat__e5-large/no_revision_available/MassiveScenarioClassification.json", + "results/intfloat__e5-large/no_revision_available/AngryTweetsClassification.json", + "results/intfloat__e5-large/no_revision_available/NordicLangClassification.json", + "results/intfloat__e5-large/no_revision_available/BornholmBitextMining.json", + "results/intfloat__e5-large/no_revision_available/ScalaNbClassification.json", + "results/intfloat__e5-large/no_revision_available/ScalaSvClassification.json", + "results/intfloat__e5-large/no_revision_available/NorwegianParliament.json", + "results/intfloat__e5-large/no_revision_available/NoRecClassification.json", + "results/intfloat__e5-large/no_revision_available/DKHateClassification.json", + "results/intfloat__e5-large/no_revision_available/ScalaDaClassification.json", + "results/intfloat__e5-large/no_revision_available/DanishPoliticalCommentsClassification.json", + "results/intfloat__e5-large/no_revision_available/LccSentimentClassification.json", + "results/intfloat__e5-large/no_revision_available/DalajClassification.json" + ], + "sentence-transformers__use-cmlm-multilingual": [ + "results/sentence-transformers__use-cmlm-multilingual/no_revision_available/BlurbsClusteringP2P.json", + "results/sentence-transformers__use-cmlm-multilingual/no_revision_available/TenKGnadClusteringS2S.json", + "results/sentence-transformers__use-cmlm-multilingual/no_revision_available/TenKGnadClusteringP2P.json", + "results/sentence-transformers__use-cmlm-multilingual/no_revision_available/BlurbsClusteringS2S.json" + ], + "distilbert__distilbert-base-uncased": [ + "results/distilbert__distilbert-base-uncased/no_revision_available/MassiveIntentClassification.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/MLSUMClusteringP2P.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/AlloProfClusteringS2S.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/SyntecReranking.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/BSARDRetrieval.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/DiaBLaBitextMining.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/MintakaRetrieval.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/SyntecRetrieval.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/MLSUMClusteringS2S.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/MassiveScenarioClassification.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/MasakhaNEWSClusteringP2P.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/AlloprofRetrieval.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/AlloprofReranking.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/FloresBitextMining.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/SummEvalFr.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/AlloProfClusteringP2P.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/MasakhaNEWSClusteringS2S.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/STS22.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/AmazonReviewsClassification.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/MTOPIntentClassification.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/HALClusteringS2S.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/MasakhaNEWSClassification.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/OpusparcusPC.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/MTOPDomainClassification.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/SICKFr.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/PawsXPairClassification.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/XPQARetrieval.json", + "results/distilbert__distilbert-base-uncased/no_revision_available/STSBenchmarkMultilingualSTS.json" + ], + "meta-llama__llama-2-7b-chat": [ + "results/meta-llama__llama-2-7b-chat/no_revision_available/Robust04InstructionRetrieval.json", + "results/meta-llama__llama-2-7b-chat/no_revision_available/News21InstructionRetrieval.json", + "results/meta-llama__llama-2-7b-chat/no_revision_available/Core17InstructionRetrieval.json" ] } \ No newline at end of file diff --git a/results.py b/results.py index 2781fceb9771cfbceedf7bffe25dd21944238a66..ec713273bc37fc420c42e4ba5854473f92fce3d0 100644 --- a/results.py +++ b/results.py @@ -1,4 +1,5 @@ """MTEB Results""" + from __future__ import annotations import json @@ -24,7 +25,205 @@ _DESCRIPTION = """Results on MTEB""" URL = "https://huggingface.co/datasets/mteb/results/resolve/main/paths.json" VERSION = datasets.Version("1.0.1") -EVAL_LANGS = ['af', 'afr-eng', 'am', "amh", 'amh-eng', 'ang-eng', 'ar', 'ar-ar', 'ara-eng', 'arq-eng', 'arz-eng', 'ast-eng', 'awa-eng', 'az', 'aze-eng', 'bel-eng', 'ben-eng', 'ber-eng', 'bn', 'bos-eng', 'bre-eng', 'bul-eng', 'cat-eng', 'cbk-eng', 'ceb-eng', 'ces-eng', 'cha-eng', 'cmn-eng', 'cor-eng', 'csb-eng', 'cy', 'cym-eng', 'da', 'dan-eng', 'de', 'de-fr', 'de-pl', 'deu-eng', 'dsb-eng', 'dtp-eng', 'el', 'ell-eng', 'en', 'en-ar', 'en-de', 'en-en', 'en-tr', 'eng', 'epo-eng', 'es', 'es-en', 'es-es', 'es-it', 'est-eng', 'eus-eng', 'fa', 'fao-eng', 'fi', 'fin-eng', 'fr', 'fr-en', 'fr-pl', 'fra', 'fra-eng', 'fry-eng', 'gla-eng', 'gle-eng', 'glg-eng', 'gsw-eng', 'hau', 'he', 'heb-eng', 'hi', 'hin-eng', 'hrv-eng', 'hsb-eng', 'hu', 'hun-eng', 'hy', 'hye-eng', 'ibo', 'id', 'ido-eng', 'ile-eng', 'ina-eng', 'ind-eng', 'is', 'isl-eng', 'it', 'it-en', 'ita-eng', 'ja', 'jav-eng', 'jpn-eng', 'jv', 'ka', 'kab-eng', 'kat-eng', 'kaz-eng', 'khm-eng', 'km', 'kn', 'ko', 'ko-ko', 'kor-eng', 'kur-eng', 'kzj-eng', 'lat-eng', 'lfn-eng', 'lit-eng', 'lin', 'lug', 'lv', 'lvs-eng', 'mal-eng', 'mar-eng', 'max-eng', 'mhr-eng', 'mkd-eng', 'ml', 'mn', 'mon-eng', 'ms', 'my', 'nb', 'nds-eng', 'nl', 'nl-ende-en', 'nld-eng', 'nno-eng', 'nob-eng', 'nov-eng', 'oci-eng', 'orm', 'orv-eng', 'pam-eng', 'pcm', 'pes-eng', 'pl', 'pl-en', 'pms-eng', 'pol-eng', 'por-eng', 'pt', 'ro', 'ron-eng', 'ru', 'run', 'rus-eng', 'sl', 'slk-eng', 'slv-eng', 'spa-eng', 'sna', 'som', 'sq', 'sqi-eng', 'srp-eng', 'sv', 'sw', 'swa', 'swe-eng', 'swg-eng', 'swh-eng', 'ta', 'tam-eng', 'tat-eng', 'te', 'tel-eng', 'tgl-eng', 'th', 'tha-eng', 'tir', 'tl', 'tr', 'tuk-eng', 'tur-eng', 'tzl-eng', 'uig-eng', 'ukr-eng', 'ur', 'urd-eng', 'uzb-eng', 'vi', 'vie-eng', 'war-eng', 'wuu-eng', 'xho', 'xho-eng', 'yid-eng', 'yor', 'yue-eng', 'zh', 'zh-CN', 'zh-TW', 'zh-en', 'zsm-eng'] +EVAL_LANGS = [ + "af", + "afr-eng", + "am", + "amh", + "amh-eng", + "ang-eng", + "ar", + "ar-ar", + "ara-eng", + "arq-eng", + "arz-eng", + "ast-eng", + "awa-eng", + "az", + "aze-eng", + "bel-eng", + "ben-eng", + "ber-eng", + "bn", + "bos-eng", + "bre-eng", + "bul-eng", + "cat-eng", + "cbk-eng", + "ceb-eng", + "ces-eng", + "cha-eng", + "cmn-eng", + "cor-eng", + "csb-eng", + "cy", + "cym-eng", + "da", + "dan-eng", + "de", + "de-fr", + "de-pl", + "deu-eng", + "dsb-eng", + "dtp-eng", + "el", + "ell-eng", + "en", + "en-ar", + "en-de", + "en-en", + "en-tr", + "eng", + "epo-eng", + "es", + "es-en", + "es-es", + "es-it", + "est-eng", + "eus-eng", + "fa", + "fao-eng", + "fi", + "fin-eng", + "fr", + "fr-en", + "fr-pl", + "fra", + "fra-eng", + "fry-eng", + "gla-eng", + "gle-eng", + "glg-eng", + "gsw-eng", + "hau", + "he", + "heb-eng", + "hi", + "hin-eng", + "hrv-eng", + "hsb-eng", + "hu", + "hun-eng", + "hy", + "hye-eng", + "ibo", + "id", + "ido-eng", + "ile-eng", + "ina-eng", + "ind-eng", + "is", + "isl-eng", + "it", + "it-en", + "ita-eng", + "ja", + "jav-eng", + "jpn-eng", + "jv", + "ka", + "kab-eng", + "kat-eng", + "kaz-eng", + "khm-eng", + "km", + "kn", + "ko", + "ko-ko", + "kor-eng", + "kur-eng", + "kzj-eng", + "lat-eng", + "lfn-eng", + "lit-eng", + "lin", + "lug", + "lv", + "lvs-eng", + "mal-eng", + "mar-eng", + "max-eng", + "mhr-eng", + "mkd-eng", + "ml", + "mn", + "mon-eng", + "ms", + "my", + "nb", + "nds-eng", + "nl", + "nl-ende-en", + "nld-eng", + "nno-eng", + "nob-eng", + "nov-eng", + "oci-eng", + "orm", + "orv-eng", + "pam-eng", + "pcm", + "pes-eng", + "pl", + "pl-en", + "pms-eng", + "pol-eng", + "por-eng", + "pt", + "ro", + "ron-eng", + "ru", + "run", + "rus-eng", + "sl", + "slk-eng", + "slv-eng", + "spa-eng", + "sna", + "som", + "sq", + "sqi-eng", + "srp-eng", + "sv", + "sw", + "swa", + "swe-eng", + "swg-eng", + "swh-eng", + "ta", + "tam-eng", + "tat-eng", + "te", + "tel-eng", + "tgl-eng", + "th", + "tha-eng", + "tir", + "tl", + "tr", + "tuk-eng", + "tur-eng", + "tzl-eng", + "uig-eng", + "ukr-eng", + "ur", + "urd-eng", + "uzb-eng", + "vi", + "vie-eng", + "war-eng", + "wuu-eng", + "xho", + "xho-eng", + "yid-eng", + "yor", + "yue-eng", + "zh", + "zh-CN", + "zh-TW", + "zh-en", + "zsm-eng", +] # v_measures key is somehow present in voyage-2-law results and is a list SKIP_KEYS = ["std", "evaluation_time", "main_score", "threshold", "v_measures", "scores_per_experiment"] @@ -32,9 +231,35 @@ SKIP_KEYS = ["std", "evaluation_time", "main_score", "threshold", "v_measures", # Use "train" split instead TRAIN_SPLIT = ["DanishPoliticalCommentsClassification"] # Use "validation" split instead -VALIDATION_SPLIT = ["AFQMC", "Cmnli", "IFlyTek", "LEMBSummScreenFDRetrieval", "MSMARCO", "MSMARCO-PL", "MultilingualSentiment", "Ocnli", "TNews"] +VALIDATION_SPLIT = [ + "AFQMC", + "Cmnli", + "IFlyTek", + "LEMBSummScreenFDRetrieval", + "MSMARCO", + "MSMARCO-PL", + "MultilingualSentiment", + "Ocnli", + "TNews", +] # Use "dev" split instead -DEV_SPLIT = ["CmedqaRetrieval", "CovidRetrieval", "DuRetrieval", "EcomRetrieval", "MedicalRetrieval", "MMarcoReranking", "MMarcoRetrieval", "MSMARCO", "MSMARCO-PL", "T2Reranking", "T2Retrieval", "VideoRetrieval", "TERRa", "MIRACLReranking", "MIRACLRetrieval"] +DEV_SPLIT = [ + "CmedqaRetrieval", + "CovidRetrieval", + "DuRetrieval", + "EcomRetrieval", + "MedicalRetrieval", + "MMarcoReranking", + "MMarcoRetrieval", + "MSMARCO", + "MSMARCO-PL", + "T2Reranking", + "T2Retrieval", + "VideoRetrieval", + "TERRa", + "MIRACLReranking", + "MIRACLRetrieval", +] # Use "test.full" split TESTFULL_SPLIT = ["OpusparcusPC"] # Use "standard" split @@ -43,219 +268,237 @@ STANDARD_SPLIT = ["BrightRetrieval"] DEVTEST_SPLIT = ["FloresBitextMining"] TEST_AVG_SPLIT = { - "LEMBNeedleRetrieval": ["test_256", "test_512", "test_1024", "test_2048", "test_4096", "test_8192", "test_16384", "test_32768"], - "LEMBPasskeyRetrieval": ["test_256", "test_512", "test_1024", "test_2048", "test_4096", "test_8192", "test_16384", "test_32768"], + "LEMBNeedleRetrieval": [ + "test_256", + "test_512", + "test_1024", + "test_2048", + "test_4096", + "test_8192", + "test_16384", + "test_32768", + ], + "LEMBPasskeyRetrieval": [ + "test_256", + "test_512", + "test_1024", + "test_2048", + "test_4096", + "test_8192", + "test_16384", + "test_32768", + ], } MODELS = [ - "Baichuan-text-embedding", - "Cohere-embed-english-v3.0", - "Cohere-embed-english-v3.0-instruct", - "Cohere-embed-multilingual-light-v3.0", - "Cohere-embed-multilingual-v3.0", - "DanskBERT", - "FollowIR-7B", - "GritLM-7B", - "GritLM-7B-noinstruct", - "LASER2", - "LLM2Vec-Llama-2-supervised", - "LLM2Vec-Llama-2-unsupervised", - "LLM2Vec-Meta-Llama-3-supervised", - "LLM2Vec-Meta-Llama-3-unsupervised", - "LLM2Vec-Mistral-supervised", - "LLM2Vec-Mistral-unsupervised", - "LLM2Vec-Sheared-Llama-supervised", - "LLM2Vec-Sheared-Llama-unsupervised", - "LaBSE", - "OpenSearch-text-hybrid", - "SFR-Embedding-Mistral", - "all-MiniLM-L6-v2", - "all-MiniLM-L6-v2-instruct", - "all-mpnet-base-v2", - "all-mpnet-base-v2-instruct", - "allenai-specter", - "bert-base-10lang-cased", - "bert-base-15lang-cased", - "bert-base-25lang-cased", - "bert-base-multilingual-cased", - "bert-base-multilingual-uncased", - "bert-base-swedish-cased", - "bert-base-uncased", - "bge-base-en-v1.5", - "bge-base-en-v1.5-instruct", - "bge-base-en", - "bge-base-zh", - "bge-base-zh-v1.5", - "bge-large-en", - "bge-large-en-v1.5", - "bge-large-en-v1.5-instruct", - "bge-large-zh", - "bge-large-zh-noinstruct", - "bge-large-zh-v1.5", - "bge-m3", - "bge-m3-instruct", - "bge-small-en-v1.5", - "bge-small-en-v1.5-instruct", - "bge-small-zh", - "bge-small-zh-v1.5", + "Alibaba-NLP__gte-Qwen1.5-7B-instruct", + "Alibaba-NLP__gte-Qwen2-7B-instruct", + "BAAI__bge-base-en", + "BAAI__bge-base-en-v1.5", + "BAAI__bge-base-en-v1.5-instruct", + "BAAI__bge-base-zh", + "BAAI__bge-base-zh-v1.5", + "BAAI__bge-large-en", + "BAAI__bge-large-en-v1.5", + "BAAI__bge-large-en-v1.5-instruct", + "BAAI__bge-large-zh", + "BAAI__bge-large-zh-noinstruct", + "BAAI__bge-large-zh-v1.5", + "BAAI__bge-m3", + "BAAI__bge-m3-instruct", + "BAAI__bge-small-en-v1.5", + "BAAI__bge-small-en-v1.5-instruct", + "BAAI__bge-small-zh", + "BAAI__bge-small-zh-v1.5", + "Cohere__Cohere-embed-english-v3.0", + "Cohere__Cohere-embed-english-v3.0-instruct", + "Cohere__Cohere-embed-multilingual-light-v3.0", + "Cohere__Cohere-embed-multilingual-v3.0", + "DeepPavlov__distilrubert-small-cased-conversational", + "DeepPavlov__rubert-base-cased", + "DeepPavlov__rubert-base-cased-sentence", + "FacebookAI__xlm-roberta-base", + "FacebookAI__xlm-roberta-large", + "Geotrend__bert-base-10lang-cased", + "Geotrend__bert-base-15lang-cased", + "Geotrend__bert-base-25lang-cased", + "Geotrend__distilbert-base-25lang-cased", + "Geotrend__distilbert-base-en-fr-cased", + "Geotrend__distilbert-base-en-fr-es-pt-it-cased", + "Geotrend__distilbert-base-fr-cased", + "GritLM__GritLM-7B", + "GritLM__GritLM-7B-noinstruct", + "KBLab__electra-small-swedish-cased-discriminator", + "KBLab__sentence-bert-swedish-cased", + "KB__bert-base-swedish-cased", + "McGill-NLP__LLM2Vec-Llama-2-7b-chat-hf-mntp-supervised", + "McGill-NLP__LLM2Vec-Llama-2-unsupervised", + "McGill-NLP__LLM2Vec-Meta-Llama-3-supervised", + "McGill-NLP__LLM2Vec-Meta-Llama-3-unsupervised", + "McGill-NLP__LLM2Vec-Mistral-supervised", + "McGill-NLP__LLM2Vec-Mistral-unsupervised", + "McGill-NLP__LLM2Vec-Sheared-Llama-supervised", + "McGill-NLP__LLM2Vec-Sheared-Llama-unsupervised", + "Muennighoff__SGPT-1.3B-weightedmean-msmarco-specb-bitfit", + "Muennighoff__SGPT-125M-weightedmean-msmarco-specb-bitfit", + "Muennighoff__SGPT-125M-weightedmean-msmarco-specb-bitfit-doc", + "Muennighoff__SGPT-125M-weightedmean-msmarco-specb-bitfit-que", + "Muennighoff__SGPT-125M-weightedmean-nli-bitfit", + "Muennighoff__SGPT-2.7B-weightedmean-msmarco-specb-bitfit", + "Muennighoff__SGPT-5.8B-weightedmean-msmarco-specb-bitfit", + "Muennighoff__SGPT-5.8B-weightedmean-msmarco-specb-bitfit-que", + "Muennighoff__SGPT-5.8B-weightedmean-nli-bitfit", + "NbAiLab__nb-bert-base", + "NbAiLab__nb-bert-large", + "Salesforce__SFR-Embedding-Mistral", + "T-Systems-onsite__cross-en-de-roberta-sentence-transformer", + "Wissam42__sentence-croissant-llm-base", + "ai-forever__sbert_large_mt_nlu_ru", + "ai-forever__sbert_large_nlu_ru", + "aliyun__OpenSearch-text-hybrid", + "almanach__camembert-base", + "almanach__camembert-large", + "amazon__titan-embed-text-v1", + "baichuan-ai__text-embedding", + "bigscience-data__sgpt-bloom-1b7-nli", + "bigscience-data__sgpt-bloom-7b1-msmarco", "bm25", "bm25s", - "camembert-base", - "camembert-large", - "contriever", - "contriever-instruct", - "contriever-base-msmarco", - "cross-en-de-roberta-sentence-transformer", - "dfm-encoder-large-v1", - "distilbert-base-25lang-cased", - "distilbert-base-en-fr-cased", - "distilbert-base-en-fr-es-pt-it-cased", - "distilbert-base-fr-cased", - "distilbert-base-uncased", - "distiluse-base-multilingual-cased-v2", - "dragon-plus", - "dragon-plus-instruct", - "e5-base", - "e5-base-4k", - "e5-base-v2", - "e5-large", - "e5-large-v2", - "e5-mistral-7b-instruct", - "e5-mistral-7b-instruct-noinstruct", - "e5-small", - "e5-small-v2", - "electra-small-nordic", - "electra-small-swedish-cased-discriminator", - "elser-v2", - "embedder-100p", - "facebook-dpr-ctx_encoder-multiset-base", - "facebookdragon-plus-context-encoder", - "flan-t5-base", - "flan-t5-large", - "flaubert_base_cased", - "flaubert_base_uncased", - "flaubert_large_cased", - "gbert-base", - "gbert-large", - "gelectra-base", - "gelectra-large", - "glove.6B.300d", - "google-gecko-256.text-embedding-preview-0409", - "google-gecko.text-embedding-preview-0409", - "gottbert-base", - "gte-Qwen1.5-7B-instruct", - "gte-Qwen2-7B-instruct", - "gtr-t5-base", - "gtr-t5-large", - "gtr-t5-xl", - "gtr-t5-xxl", - "herbert-base-retrieval-v2", - "instructor-base", - "instructor-large", - "instructor-xl", - "jina-embeddings-v2-base-en", - "komninos", - "llama-2-7b-chat", - "luotuo-bert-medium", - "m3e-base", - "m3e-large", - "mistral-7b-instruct-v0.2", - "mistral-embed", - "monobert-large-msmarco", - "monot5-3b-msmarco-10k", - "monot5-base-msmarco-10k", - "msmarco-bert-co-condensor", - "multi-qa-MiniLM-L6-cos-v1", - "multilingual-e5-base", - "multilingual-e5-large", - "multilingual-e5-large-instruct", - "multilingual-e5-small", - "mxbai-embed-large-v1", - "nb-bert-base", - "nb-bert-large", - "nomic-embed-text-v1", - "nomic-embed-text-v1.5-128", - "nomic-embed-text-v1.5-256", - "nomic-embed-text-v1.5-512", - "nomic-embed-text-v1.5-64", - "norbert3-base", - "norbert3-large", - "paraphrase-multilingual-MiniLM-L12-v2", - "paraphrase-multilingual-mpnet-base-v2", - "rubert-tiny", - "rubert-tiny2", - "sbert_large_mt_nlu_ru", - "sbert_large_nlu_ru", - "sentence-bert-swedish-cased", - "sentence-camembert-base", - "sentence-camembert-large", - "sentence-croissant-llm-base", - "sentence-t5-base", - "sentence-t5-large", - "sentence-t5-xl", - "sentence-t5-xxl", - "all-MiniLM-L12-v2", - "sgpt-bloom-1b7-nli", - "sgpt-bloom-7b1-msmarco", - "SGPT-125M-weightedmean-nli-bitfit", - "SGPT-1.3B-weightedmean-msmarco-specb-bitfit", - "SGPT-5.8B-weightedmean-msmarco-specb-bitfit-que", - "SGPT-5.8B-weightedmean-msmarco-specb-bitfit", - "SGPT-5.8B-weightedmean-nli-bitfit", - "SGPT-2.7B-weightedmean-msmarco-specb-bitfit", - "SGPT-125M-weightedmean-msmarco-specb-bitfit-que", - "SGPT-125M-weightedmean-msmarco-specb-bitfit-doc", - "SGPT-125M-weightedmean-msmarco-specb-bitfit", - "silver-retriever-base-v1", - "st-polish-paraphrase-from-distilroberta", - "st-polish-paraphrase-from-mpnet", - "sup-simcse-bert-base-uncased", - "tart-dual-contriever-msmarco", - "tart-full-flan-t5-xl", - "text-embedding-3-large", - "text-embedding-3-large-instruct", - "text-embedding-3-large-256", - "text-embedding-3-small", - "text-embedding-3-small-instruct", - "text-embedding-ada-002", - "text-embedding-ada-002-instruct", - "text-search-ada-001", - "text-search-ada-doc-001", - "text-search-babbage-001", - "text-search-curie-001", - "text-search-davinci-001", - "text-similarity-ada-001", - "text-similarity-babbage-001", - "text-similarity-curie-001", - "text-similarity-davinci-001", - "text2vec-base-chinese", - "text2vec-base-multilingual", - "text2vec-large-chinese", - "titan-embed-text-v1", - "udever-bloom-1b1", - "udever-bloom-560m", - "universal-sentence-encoder-multilingual-3", - "universal-sentence-encoder-multilingual-large-3", - "unsup-simcse-bert-base-uncased", - "use-cmlm-multilingual", - "voyage-2", - "voyage-code-2", - "voyage-large-2-instruct", - "voyage-law-2", - "voyage-lite-01-instruct", - "voyage-lite-02-instruct", - "voyage-multilingual-2", - "xlm-roberta-base", - "xlm-roberta-large", - "deberta-v1-base", - "USER-bge-m3", - "USER-base", - "rubert-tiny-turbo", - "LaBSE-ru-turbo", - "distilrubert-small-cased-conversational", - "rubert-base-cased", - "rubert-base-cased-sentence", - "LaBSE-en-ru", + "castorini__monobert-large-msmarco", + "castorini__monot5-3b-msmarco-10k", + "castorini__monot5-base-msmarco-10k", + "chcaa__dfm-encoder-large-v1", + "cointegrated__LaBSE-en-ru", + "cointegrated__rubert-tiny", + "cointegrated__rubert-tiny2", + "dangvantuan__sentence-camembert-base", + "dangvantuan__sentence-camembert-large", + "deepfile__embedder-100p", + "deepset__gbert-base", + "deepset__gbert-large", + "deepset__gelectra-base", + "deepset__gelectra-large", + "deepvk__USER-base", + "deepvk__USER-bge-m3", + "deepvk__deberta-v1-base", + "distilbert__distilbert-base-uncased", + "dwzhu__e5-base-4k", + "elastic__elser-v2", + "facebook__contriever", + "facebook__contriever-instruct", + "facebook__dpr-ctx_encoder-multiset-base", + "facebook__dragon-plus-context-encoder", + "facebook__tart-full-flan-t5-xl", + "facebookresearch__LASER2", + "facebookresearch__dragon-plus", + "facebookresearch__dragon-plus-instruct", + "flaubert__flaubert_base_cased", + "flaubert__flaubert_base_uncased", + "flaubert__flaubert_large_cased", + "google-bert__bert-base-multilingual-cased", + "google-bert__bert-base-multilingual-uncased", + "google-bert__bert-base-uncased", + "google-gecko__text-embedding-preview-0409", + "google-gecko__text-embedding-preview-0409-256", + "google__flan-t5-base", + "google__flan-t5-large", + "hkunlp__instructor-base", + "hkunlp__instructor-large", + "hkunlp__instructor-xl", + "intfloat__e5-base", + "intfloat__e5-base-v2", + "intfloat__e5-large", + "intfloat__e5-large-v2", + "intfloat__e5-mistral-7b-instruct", + "intfloat__e5-mistral-7b-instruct-noinstruct", + "intfloat__e5-small", + "intfloat__e5-small-v2", + "intfloat__multilingual-e5-base", + "intfloat__multilingual-e5-large", + "intfloat__multilingual-e5-large-instruct", + "intfloat__multilingual-e5-small", + "ipipan__herbert-base-retrieval-v2", + "ipipan__silver-retriever-base-v1", + "izhx__udever-bloom-1b1", + "izhx__udever-bloom-560m", + "jhu-clsp__FollowIR-7B", + "jinaai__jina-embeddings-v2-base-en", + "jonfd__electra-small-nordic", + "ltg__norbert3-base", + "ltg__norbert3-large", + "meta-llama__llama-2-7b-chat", + "mistral__mistral-embed", + "mistralai__mistral-7b-instruct-v0.2", + "mixedbread-ai__mxbai-embed-large-v1", + "moka-ai__m3e-base", + "moka-ai__m3e-large", + "nomic-ai__nomic-embed-text-v1", + "nomic-ai__nomic-embed-text-v1.5-128", + "nomic-ai__nomic-embed-text-v1.5-256", + "nomic-ai__nomic-embed-text-v1.5-512", + "nomic-ai__nomic-embed-text-v1.5-64", + "nthakur__contriever-base-msmarco", + "openai__text-embedding-3-large", + "openai__text-embedding-3-large-256", + "openai__text-embedding-3-large-instruct", + "openai__text-embedding-3-small-instruct", + "openai__text-embedding-ada-002", + "openai__text-embedding-ada-002-instruct", + "openai__text-search-ada-001", + "openai__text-search-ada-doc-001", + "openai__text-search-babbage-001", + "openai__text-search-curie-001", + "openai__text-search-davinci-001", + "openai__text-similarity-ada-001", + "openai__text-similarity-babbage-001", + "openai__text-similarity-curie-001", + "openai__text-similarity-davinci-001", + "openai__text-embedding-3-small", + "orionweller__tart-dual-contriever-msmarco", + "princeton-nlp__sup-simcse-bert-base-uncased", + "princeton-nlp__unsup-simcse-bert-base-uncased", + "sdadas__st-polish-paraphrase-from-distilroberta", + "sdadas__st-polish-paraphrase-from-mpnet", + "sentence-transformers__LaBSE", + "sentence-transformers__all-MiniLM-L12-v2", + "sentence-transformers__all-MiniLM-L6-v2", + "sentence-transformers__all-MiniLM-L6-v2-instruct", + "sentence-transformers__all-mpnet-base-v2", + "sentence-transformers__all-mpnet-base-v2-instruct", + "sentence-transformers__allenai-specter", + "sentence-transformers__average_word_embeddings_glove.6B.300d", + "sentence-transformers__average_word_embeddings_komninos", + "sentence-transformers__distiluse-base-multilingual-cased-v2", + "sentence-transformers__gtr-t5-base", + "sentence-transformers__gtr-t5-large", + "sentence-transformers__gtr-t5-xl", + "sentence-transformers__gtr-t5-xxl", + "sentence-transformers__msmarco-bert-co-condensor", + "sentence-transformers__multi-qa-MiniLM-L6-cos-v1", + "sentence-transformers__paraphrase-multilingual-MiniLM-L12-v2", + "sentence-transformers__paraphrase-multilingual-mpnet-base-v2", + "sentence-transformers__sentence-t5-base", + "sentence-transformers__sentence-t5-large", + "sentence-transformers__sentence-t5-xl", + "sentence-transformers__sentence-t5-xxl", + "sentence-transformers__use-cmlm-multilingual", + "sergeyzh__LaBSE-ru-turbo", + "sergeyzh__rubert-tiny-turbo", + "shibing624__text2vec-base-chinese", + "shibing624__text2vec-base-multilingual", + "shibing624__text2vec-large-chinese", + "silk-road__luotuo-bert-medium", + "uklfr__gottbert-base", + "vesteinn__DanskBERT", + "voyageai__voyage-2", + "voyageai__voyage-code-2", + "voyageai__voyage-large-2-instruct", + "voyageai__voyage-law-2", + "voyageai__voyage-lite-01-instruct", + "voyageai__voyage-lite-02-instruct", + "voyageai__voyage-multilingual-2", + "vprelovac__universal-sentence-encoder-multilingual-3", + "vprelovac__universal-sentence-encoder-multilingual-large-3", ] @@ -269,6 +512,7 @@ def get_model_for_current_dir(dir_name: str) -> str | None: # Needs to be run whenever new files are added def get_paths(): import collections, json, os + files = collections.defaultdict(list) for model_dir in os.listdir("results"): results_model_dir = os.path.join("results", model_dir) @@ -283,7 +527,9 @@ def get_paths(): if not os.path.isdir(os.path.join(results_model_dir, revision_folder)): continue for res_file in os.listdir(os.path.join(results_model_dir, revision_folder)): - if (res_file.endswith(".json")) and not(res_file.endswith(("overall_results.json", "model_meta.json"))): + if (res_file.endswith(".json")) and not ( + res_file.endswith(("overall_results.json", "model_meta.json")) + ): results_model_file = os.path.join(results_model_dir, revision_folder, res_file) files[model_name].append(results_model_file) with open("paths.json", "w") as f: @@ -327,12 +573,7 @@ class MTEBResults(datasets.GeneratorBasedBuilder): with open(path_file) as f: files = json.load(f) downloaded_files = dl_manager.download_and_extract(files[self.config.name]) - return [ - datasets.SplitGenerator( - name=datasets.Split.TEST, - gen_kwargs={'filepath': downloaded_files} - ) - ] + return [datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files})] def _generate_examples(self, filepath): """This function returns the examples in the raw (text) form.""" @@ -356,7 +597,7 @@ class MTEBResults(datasets.GeneratorBasedBuilder): split = "dev" elif (ds_name in TESTFULL_SPLIT) and ("test.full" in res_dict): split = "test.full" - elif (ds_name in STANDARD_SPLIT): + elif ds_name in STANDARD_SPLIT: split = [] if "standard" in res_dict: split += ["standard"] @@ -364,7 +605,7 @@ class MTEBResults(datasets.GeneratorBasedBuilder): split += ["long"] elif (ds_name in DEVTEST_SPLIT) and ("devtest" in res_dict): split = "devtest" - elif (ds_name in TEST_AVG_SPLIT): + elif ds_name in TEST_AVG_SPLIT: # Average splits res_dict = {} for split in TEST_AVG_SPLIT[ds_name]: @@ -385,7 +626,8 @@ class MTEBResults(datasets.GeneratorBasedBuilder): for k, v in res_dict[split][0].items(): if k in ["hf_subset", "languages"]: res_dict[k] = v - if not isinstance(v, float): continue + if not isinstance(v, float): + continue v /= len(TEST_AVG_SPLIT[ds_name]) if k not in res_dict: res_dict[k] = v @@ -414,41 +656,48 @@ class MTEBResults(datasets.GeneratorBasedBuilder): if not lang: lang = subset for metric, score in res.items(): - if metric in SKIP_KEYS: continue + if metric in SKIP_KEYS: + continue if isinstance(score, dict): # Legacy format with e.g. {cosine: {spearman: ...}} # Now it is {cosine_spearman: ...} for k, v in score.items(): if not isinstance(v, float): - print(f'WARNING: Expected float, got {v} for {ds_name} {lang} {metric} {k}') + print(f"WARNING: Expected float, got {v} for {ds_name} {lang} {metric} {k}") continue - if metric in SKIP_KEYS: continue - out.append({ - "mteb_dataset_name": ds_name, - "eval_language": lang, - "metric": metric + "_" + k, - "score": v * 100, - "hf_subset": subset, - }) + if metric in SKIP_KEYS: + continue + out.append( + { + "mteb_dataset_name": ds_name, + "eval_language": lang, + "metric": metric + "_" + k, + "score": v * 100, + "hf_subset": subset, + } + ) else: if not isinstance(score, float): - print(f'WARNING: Expected float, got {score} for {ds_name} {lang} {metric}') + print(f"WARNING: Expected float, got {score} for {ds_name} {lang} {metric}") continue - out.append({ - "mteb_dataset_name": ds_name, - "eval_language": lang, - "metric": metric, - "score": score * 100, - "split": split, - "hf_subset": subset, - }) + out.append( + { + "mteb_dataset_name": ds_name, + "eval_language": lang, + "metric": metric, + "score": score * 100, + "split": split, + "hf_subset": subset, + } + ) ### Old MTEB format ### else: is_multilingual = any(x in res_dict for x in EVAL_LANGS) langs = res_dict.keys() if is_multilingual else ["en"] for lang in langs: - if lang in SKIP_KEYS: continue + if lang in SKIP_KEYS: + continue test_result_lang = res_dict.get(lang) if is_multilingual else res_dict subset = test_result_lang.pop("hf_subset", "") if subset == "" and is_multilingual: @@ -457,16 +706,20 @@ class MTEBResults(datasets.GeneratorBasedBuilder): if not isinstance(score, dict): score = {metric: score} for sub_metric, sub_score in score.items(): - if any(x in sub_metric for x in SKIP_KEYS): continue - if isinstance(sub_score, dict): continue - out.append({ - "mteb_dataset_name": ds_name, - "eval_language": lang if is_multilingual else "", - "metric": f"{metric}_{sub_metric}" if metric != sub_metric else metric, - "score": sub_score * 100, - "split": split, - "hf_subset": subset, - }) + if any(x in sub_metric for x in SKIP_KEYS): + continue + if isinstance(sub_score, dict): + continue + out.append( + { + "mteb_dataset_name": ds_name, + "eval_language": lang if is_multilingual else "", + "metric": f"{metric}_{sub_metric}" if metric != sub_metric else metric, + "score": sub_score * 100, + "split": split, + "hf_subset": subset, + } + ) for idx, row in enumerate(sorted(out, key=lambda x: x["mteb_dataset_name"])): yield idx, row diff --git a/results/gte-Qwen1.5-7B-instruct/no_revision_available/AFQMC.json b/results/Alibaba-NLP__gte-Qwen1.5-7B-instruct/no_revision_available/AFQMC.json similarity index 100% rename from results/gte-Qwen1.5-7B-instruct/no_revision_available/AFQMC.json rename to 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similarity index 100% rename from results/unsup-simcse-bert-base-uncased/no_revision_available/SummEval.json rename to results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/SummEval.json diff --git a/results/unsup-simcse-bert-base-uncased/no_revision_available/TRECCOVID.json b/results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/TRECCOVID.json similarity index 100% rename from results/unsup-simcse-bert-base-uncased/no_revision_available/TRECCOVID.json rename to results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/TRECCOVID.json diff --git a/results/unsup-simcse-bert-base-uncased/no_revision_available/Touche2020.json b/results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/Touche2020.json similarity index 100% rename from results/unsup-simcse-bert-base-uncased/no_revision_available/Touche2020.json rename to results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/Touche2020.json diff --git a/results/unsup-simcse-bert-base-uncased/no_revision_available/ToxicConversationsClassification.json b/results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/ToxicConversationsClassification.json similarity index 100% rename from results/unsup-simcse-bert-base-uncased/no_revision_available/ToxicConversationsClassification.json rename to results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/ToxicConversationsClassification.json diff --git a/results/unsup-simcse-bert-base-uncased/no_revision_available/TweetSentimentExtractionClassification.json b/results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/TweetSentimentExtractionClassification.json similarity index 100% rename from results/unsup-simcse-bert-base-uncased/no_revision_available/TweetSentimentExtractionClassification.json rename to results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/TweetSentimentExtractionClassification.json diff --git a/results/unsup-simcse-bert-base-uncased/no_revision_available/TwentyNewsgroupsClustering.json b/results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/TwentyNewsgroupsClustering.json similarity index 100% rename from results/unsup-simcse-bert-base-uncased/no_revision_available/TwentyNewsgroupsClustering.json rename to results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/TwentyNewsgroupsClustering.json diff --git a/results/unsup-simcse-bert-base-uncased/no_revision_available/TwitterSemEval2015.json b/results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/TwitterSemEval2015.json similarity index 100% rename from results/unsup-simcse-bert-base-uncased/no_revision_available/TwitterSemEval2015.json rename to results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/TwitterSemEval2015.json diff --git a/results/unsup-simcse-bert-base-uncased/no_revision_available/TwitterURLCorpus.json b/results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/TwitterURLCorpus.json similarity index 100% rename from results/unsup-simcse-bert-base-uncased/no_revision_available/TwitterURLCorpus.json rename to results/princeton-nlp__unsup-simcse-bert-base-uncased/no_revision_available/TwitterURLCorpus.json diff --git a/results/rename_and_move_over.py b/results/rename_and_move_over.py index 8b263f56642de4e2fcc06613dd72e4caa6c855db..18f01269cf9357722909bdd74e6d525db394852f 100644 --- a/results/rename_and_move_over.py +++ b/results/rename_and_move_over.py @@ -2,13 +2,13 @@ import os import glob import tqdm -for folder in tqdm.tqdm(glob.glob('results/*')): +for folder in tqdm.tqdm(glob.glob("results/*")): if not os.path.isdir(folder): continue - + # move all files in that folder into a new folder called "no_revision_available" os.makedirs(os.path.join(folder, "no_revision_available"), exist_ok=True) os.system(f"mv {os.path.join(folder, '*')} {os.path.join(folder, 'no_revision_available')}") # now move it over to /home/hltcoe/oweller/my_exps/mteb_public/results - os.system(f"mv {folder} /home/hltcoe/oweller/my_exps/mteb_public/results") \ No newline at end of file + os.system(f"mv {folder} /home/hltcoe/oweller/my_exps/mteb_public/results") diff --git a/results/st-polish-paraphrase-from-distilroberta/no_revision_available/8TagsClustering.json b/results/sdadas__st-polish-paraphrase-from-distilroberta/no_revision_available/8TagsClustering.json similarity index 100% rename from results/st-polish-paraphrase-from-distilroberta/no_revision_available/8TagsClustering.json rename to results/sdadas__st-polish-paraphrase-from-distilroberta/no_revision_available/8TagsClustering.json diff --git a/results/st-polish-paraphrase-from-distilroberta/no_revision_available/AllegroReviews.json b/results/sdadas__st-polish-paraphrase-from-distilroberta/no_revision_available/AllegroReviews.json similarity index 100% rename from results/st-polish-paraphrase-from-distilroberta/no_revision_available/AllegroReviews.json rename to results/sdadas__st-polish-paraphrase-from-distilroberta/no_revision_available/AllegroReviews.json diff --git a/results/st-polish-paraphrase-from-distilroberta/no_revision_available/ArguAna-PL.json b/results/sdadas__st-polish-paraphrase-from-distilroberta/no_revision_available/ArguAna-PL.json similarity index 100% rename from results/st-polish-paraphrase-from-distilroberta/no_revision_available/ArguAna-PL.json rename to results/sdadas__st-polish-paraphrase-from-distilroberta/no_revision_available/ArguAna-PL.json diff --git a/results/st-polish-paraphrase-from-distilroberta/no_revision_available/CBD.json b/results/sdadas__st-polish-paraphrase-from-distilroberta/no_revision_available/CBD.json similarity index 100% rename from results/st-polish-paraphrase-from-distilroberta/no_revision_available/CBD.json rename to results/sdadas__st-polish-paraphrase-from-distilroberta/no_revision_available/CBD.json diff --git a/results/st-polish-paraphrase-from-distilroberta/no_revision_available/CDSC-E.json b/results/sdadas__st-polish-paraphrase-from-distilroberta/no_revision_available/CDSC-E.json similarity index 100% rename from results/st-polish-paraphrase-from-distilroberta/no_revision_available/CDSC-E.json rename to results/sdadas__st-polish-paraphrase-from-distilroberta/no_revision_available/CDSC-E.json diff --git a/results/st-polish-paraphrase-from-distilroberta/no_revision_available/CDSC-R.json b/results/sdadas__st-polish-paraphrase-from-distilroberta/no_revision_available/CDSC-R.json similarity index 100% rename from results/st-polish-paraphrase-from-distilroberta/no_revision_available/CDSC-R.json rename to results/sdadas__st-polish-paraphrase-from-distilroberta/no_revision_available/CDSC-R.json diff --git a/results/st-polish-paraphrase-from-distilroberta/no_revision_available/DBPedia-PL.json 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a/results/universal-sentence-encoder-multilingual-large-3/no_revision_available/STS22.json b/results/vprelovac__universal-sentence-encoder-multilingual-large-3/no_revision_available/STS22.json similarity index 100% rename from results/universal-sentence-encoder-multilingual-large-3/no_revision_available/STS22.json rename to results/vprelovac__universal-sentence-encoder-multilingual-large-3/no_revision_available/STS22.json diff --git a/results/universal-sentence-encoder-multilingual-large-3/no_revision_available/STSBenchmarkMultilingualSTS.json b/results/vprelovac__universal-sentence-encoder-multilingual-large-3/no_revision_available/STSBenchmarkMultilingualSTS.json similarity index 100% rename from results/universal-sentence-encoder-multilingual-large-3/no_revision_available/STSBenchmarkMultilingualSTS.json rename to results/vprelovac__universal-sentence-encoder-multilingual-large-3/no_revision_available/STSBenchmarkMultilingualSTS.json diff --git a/results/universal-sentence-encoder-multilingual-large-3/no_revision_available/SummEvalFr.json b/results/vprelovac__universal-sentence-encoder-multilingual-large-3/no_revision_available/SummEvalFr.json similarity index 100% rename from results/universal-sentence-encoder-multilingual-large-3/no_revision_available/SummEvalFr.json rename to results/vprelovac__universal-sentence-encoder-multilingual-large-3/no_revision_available/SummEvalFr.json diff --git a/results/universal-sentence-encoder-multilingual-large-3/no_revision_available/SyntecReranking.json b/results/vprelovac__universal-sentence-encoder-multilingual-large-3/no_revision_available/SyntecReranking.json similarity index 100% rename from results/universal-sentence-encoder-multilingual-large-3/no_revision_available/SyntecReranking.json rename to results/vprelovac__universal-sentence-encoder-multilingual-large-3/no_revision_available/SyntecReranking.json diff --git a/results/universal-sentence-encoder-multilingual-large-3/no_revision_available/SyntecRetrieval.json b/results/vprelovac__universal-sentence-encoder-multilingual-large-3/no_revision_available/SyntecRetrieval.json similarity index 100% rename from results/universal-sentence-encoder-multilingual-large-3/no_revision_available/SyntecRetrieval.json rename to results/vprelovac__universal-sentence-encoder-multilingual-large-3/no_revision_available/SyntecRetrieval.json diff --git a/results/universal-sentence-encoder-multilingual-large-3/no_revision_available/XPQARetrieval.json b/results/vprelovac__universal-sentence-encoder-multilingual-large-3/no_revision_available/XPQARetrieval.json similarity index 100% rename from results/universal-sentence-encoder-multilingual-large-3/no_revision_available/XPQARetrieval.json rename to results/vprelovac__universal-sentence-encoder-multilingual-large-3/no_revision_available/XPQARetrieval.json diff --git a/scripts/convert_bright.py b/scripts/convert_bright.py index ecf65a19f44fa78a54b2d47fd1e85cf733172196..36a884ef9c4747b8d78257fe558b512c896f50e6 100644 --- a/scripts/convert_bright.py +++ b/scripts/convert_bright.py @@ -2,12 +2,12 @@ import json import os REPLACE_MAP = { - "NDCG": 'ndcg', - "MAP": 'map', - "MRR": 'mrr', - "RECALL": 'recall', - "Recall": 'recall', - "P": 'precision', + "NDCG": "ndcg", + "MAP": "map", + "MRR": "mrr", + "RECALL": "recall", + "Recall": "recall", + "P": "precision", } MODEL_TO_MODEL = { @@ -26,8 +26,14 @@ MODEL_TO_MODEL = { "sf": "SFR-Embedding-Mistral", "voyage": "voyage-large-2-instruct", } -folders = os.listdir('bright_scores/main') + os.listdir('bright_scores/long_context') -models = set([x.split("_")[-3] for x in folders if (os.path.isdir('bright_scores/main/' + x) or os.path.isdir('bright_scores/long_context/' + x))]) +folders = os.listdir("bright_scores/main") + os.listdir("bright_scores/long_context") +models = set( + [ + x.split("_")[-3] + for x in folders + if (os.path.isdir("bright_scores/main/" + x) or os.path.isdir("bright_scores/long_context/" + x)) + ] +) print(models) for model in models: print(f"Converting {model}") @@ -35,21 +41,21 @@ for model in models: "dataset_revision": "a75a0eb483f6a5233a6efc2d63d71540a4443dfb", "evaluation_time": 0, "kg_co2_emissions": None, - "mteb_version": "1.12.79", - "scores": { - "standard": [], - "long": [] - }, + "mteb_version": "1.12.79", + "scores": {"standard": [], "long": []}, "task_name": "BrightRetrieval", } for folder in [ - x for x in folders if (os.path.isdir('bright_scores/main/' + x) or os.path.isdir('bright_scores/long_context/' + x)) and (x.split("_")[-3] == model) + x + for x in folders + if (os.path.isdir("bright_scores/main/" + x) or os.path.isdir("bright_scores/long_context/" + x)) + and (x.split("_")[-3] == model) ]: - if os.path.isdir('bright_scores/main/' + folder): - results_path = os.path.join('bright_scores/main', folder, 'results.json') + if os.path.isdir("bright_scores/main/" + folder): + results_path = os.path.join("bright_scores/main", folder, "results.json") split = "standard" else: - results_path = os.path.join('bright_scores/long_context', folder, 'results.json') + results_path = os.path.join("bright_scores/long_context", folder, "results.json") assert "long_True" in folder, folder split = "long" @@ -61,19 +67,17 @@ for model in models: elif len(folder.split("_")) == 5: subset = folder.split("_")[0] + "_" + folder.split("_")[1] - result_template['scores'][split].append( + result_template["scores"][split].append( { "hf_subset": subset, "languages": ["eng-Latn"], "main_score": results["NDCG@10"], - **{"_at_".join([REPLACE_MAP.get(x, x) for x in k.split("@")]): v for k,v in results.items()} + **{"_at_".join([REPLACE_MAP.get(x, x) for x in k.split("@")]): v for k, v in results.items()}, } ) - + model_folder = MODEL_TO_MODEL[model] os.makedirs(f"results/{model_folder}/no_revision_available", exist_ok=True) print(f"Writing to: results/{model_folder}/no_revision_available/BrightRetrieval.json") with open(f"results/{model_folder}/no_revision_available/BrightRetrieval.json", "w") as f: json.dump(result_template, f, indent=4) - - diff --git a/scripts/merge_same_model.py b/scripts/merge_same_model.py index 70b02b2b683ed310fb8723d14b4b52fa0b2f8129..838b3c32870143de2d25a38ba00807f152e0b0cc 100644 --- a/scripts/merge_same_model.py +++ b/scripts/merge_same_model.py @@ -7,30 +7,29 @@ def line_count(file): with open(file) as f: return sum(1 for _ in f) -for folder in glob.glob('results/*'): + +for folder in glob.glob("results/*"): if not os.path.isdir(folder): continue - print(f"Processing {folder}") # create the subfolder if it doesn't exist - for subfolder in glob.glob(os.path.join(folder + "-1", '*')): + for subfolder in glob.glob(os.path.join(folder + "-1", "*")): if not os.path.isdir(subfolder): continue # if it doesn't exist in the original, create it - if not os.path.isdir(subfolder.replace('-1', '')): - os.makedirs(subfolder.replace('-1', ''), exist_ok=True) - + if not os.path.isdir(subfolder.replace("-1", "")): + os.makedirs(subfolder.replace("-1", ""), exist_ok=True) # if there is the same folder name but with -1 at the end, we need a merge - if os.path.isdir(folder + '-1'): + if os.path.isdir(folder + "-1"): # copy each file over, unless it is already there, in which case choose the longest one - for file in tqdm.tqdm(glob.glob(os.path.join(folder + '-1', '*', "*.json"))): - if os.path.exists(file.replace('-1', '')): + for file in tqdm.tqdm(glob.glob(os.path.join(folder + "-1", "*", "*.json"))): + if os.path.exists(file.replace("-1", "")): line_count_1 = line_count(file) - line_count_2 = line_count(file.replace('-1', '')) + line_count_2 = line_count(file.replace("-1", "")) if line_count_1 > line_count_2: os.system(f"mv {file} {file.replace('-1', '')}") @@ -44,4 +43,4 @@ This script merges two model directories that are the same except one ends with I renamed all files to end with "-1" because we can't have duplicate filenames. Then we need some script to merge their contents (which is this). So first rename all model folders then run this. Then go through and remove the -1 from ones that are new and thus werent merged -""" \ No newline at end of file +""" diff --git a/scripts/normalize_results_folder.py b/scripts/normalize_results_folder.py index 0570de058ad132c83815ac762d40ff94d21a8d94..7ff3c698210ae8dddbe51b38bf197cfe5916ea56 100644 --- a/scripts/normalize_results_folder.py +++ b/scripts/normalize_results_folder.py @@ -44,15 +44,13 @@ def resolve_conflict_result(current_path: Path, expected_path: Path) -> None: # check version and keep the newest c_version = c_res.mteb_version e_version = e_res.mteb_version - + if Version(c_version) > Version(e_version): logger.info("Newer version of result file, moving") expected_path.parent.mkdir(parents=True, exist_ok=True) current_path.rename(expected_path) elif Version(c_version) == Version(e_version): - logger.info( - "Same version of result file, removing, but scores are different. Please resolve manually." - ) + logger.info("Same version of result file, removing, but scores are different. Please resolve manually.") logger.info(f"Old scores: {c_res.scores}") logger.info(f"New scores: {e_res.scores}") else: diff --git a/scripts/remove_ablations.py b/scripts/remove_ablations.py index ea7e00cdb7161cf26ba93f5c7fac7c4e0c202aa7..469c541c207aa6cc81e9dc1fdb844ed5790ce1bb 100644 --- a/scripts/remove_ablations.py +++ b/scripts/remove_ablations.py @@ -12,7 +12,6 @@ for file in tqdm.tqdm(glob.glob("results/*/*.json")): data = json.load(fin) if "individual" in data["test"]: del data["test"]["individual"] - + with open(file, "w") as fout: json.dump(data, fout, indent=2) - diff --git a/tests/test_correct_folder_structure.py b/tests/test_correct_folder_structure.py index ae45999825945d38c7e48952d4ec54295118b2bd..ed4f57ebc4f36e1009033ffd07e3d04c0759140d 100644 --- a/tests/test_correct_folder_structure.py +++ b/tests/test_correct_folder_structure.py @@ -34,217 +34,220 @@ def test_correct_folder_structure(): folders_without_meta = [ # please do not add to this list it is only intended for backwards compatibility. Future results should have a model_meta.json file - ("text-search-davinci-001", "no_revision_available"), - ("LLM2Vec-Llama-2-unsupervised", "no_revision_available"), - ("text-search-babbage-001", "no_revision_available"), - ("instructor-base", "no_revision_available"), - ("embedder-100p", "no_revision_available"), - ("text-embedding-ada-002-instruct", "no_revision_available"), - ("bge-m3-instruct", "5617a9f61b028005a4858fdac845db406aefb181"), - ("xlm-roberta-large", "no_revision_available"), - ("voyage-2", "no_revision_available"), - ("text-search-ada-001", "no_revision_available"), - ("gtr-t5-large", "no_revision_available"), - ("sentence-t5-xxl", "no_revision_available"), - ("text-embedding-3-small-instruct", "no_revision_available"), - ("bge-m3", "no_revision_available"), - ("voyage-lite-02-instruct", "no_revision_available"), - ("text-similarity-ada-001", "no_revision_available"), - ("LLM2Vec-Sheared-Llama-supervised", "no_revision_available"), - ("e5-base", "no_revision_available"), - ("bge-small-zh-v1.5", "no_revision_available"), - ("bge-base-en", "no_revision_available"), - ("electra-small-swedish-cased-discriminator", "no_revision_available"), - ("nomic-embed-text-v1.5-512", "no_revision_available"), - ("LLM2Vec-Mistral-unsupervised", "no_revision_available"), - ("voyage-law-2", "no_revision_available"), - ("e5-base-4k", "no_revision_available"), - ("cross-en-de-roberta-sentence-transformer", "no_revision_available"), - ("sentence-camembert-base", "no_revision_available"), - ("SGPT-5.8B-weightedmean-nli-bitfit", "no_revision_available"), - ("camembert-large", "no_revision_available"), - ("SGPT-125M-weightedmean-msmarco-specb-bitfit-doc", "no_revision_available"), - ("Baichuan-text-embedding", "no_revision_available"), - ("LaBSE", "e34fab64a3011d2176c99545a93d5cbddc9a91b7"), - ("LaBSE", "no_revision_available"), - ("sentence-croissant-llm-base", "no_revision_available"), - ("bert-base-25lang-cased", "no_revision_available"), - ("sgpt-bloom-7b1-msmarco", "no_revision_available"), - ("electra-small-nordic", "no_revision_available"), - ("SGPT-5.8B-weightedmean-msmarco-specb-bitfit", "no_revision_available"), - ("distilbert-base-uncased", "no_revision_available"), - ("LLM2Vec-Meta-Llama-3-supervised", "no_revision_available"), - ("text-embedding-3-large", "no_revision_available"), - ("bert-base-10lang-cased", "no_revision_available"), - ("sentence-t5-large", "no_revision_available"), - ("m3e-base", "no_revision_available"), - ("e5-mistral-7b-instruct", "no_revision_available"), - ("camembert-base", "no_revision_available"), - ("universal-sentence-encoder-multilingual-3", "no_revision_available"), - ("sentence-camembert-large", "no_revision_available"), - ("gelectra-large", "no_revision_available"), - ("e5-large-v2", "no_revision_available"), - ("e5-large-v2", "b322e09026e4ea05f42beadf4d661fb4e101d311"), - ("m3e-large", "no_revision_available"), - ("llama-2-7b-chat", "no_revision_available"), - ("sgpt-bloom-1b7-nli", "no_revision_available"), - ("all-mpnet-base-v2", "84f2bcc00d77236f9e89c8a360a00fb1139bf47d"), - ("sentence-t5-xl", "no_revision_available"), - ("distilbert-base-en-fr-cased", "no_revision_available"), - ("text-embedding-ada-002", "no_revision_available"), - ("bge-small-en-v1.5-instruct", "5c38ec7c405ec4b44b94cc5a9bb96e735b38267a"), - ("text2vec-base-multilingual", "no_revision_available"), - ("multi-qa-MiniLM-L6-cos-v1", "no_revision_available"), - ("jina-embeddings-v2-base-en", "no_revision_available"), - ("mistral-7b-instruct-v0.2", "no_revision_available"), - ("monot5-base-msmarco-10k", "no_revision_available"), - ("gte-Qwen2-7B-instruct", "no_revision_available"), - ("bert-base-multilingual-uncased", "no_revision_available"), - ("distiluse-base-multilingual-cased-v2", "no_revision_available"), - ("distiluse-base-multilingual-cased-v2", ".gitkeep"), - ("bge-base-zh-v1.5", "no_revision_available"), - ("google-gecko.text-embedding-preview-0409", "no_revision_available"), - ("text-search-curie-001", "no_revision_available"), - ("sup-simcse-bert-base-uncased", "no_revision_available"), - ("bge-base-en-v1.5-instruct", "a5beb1e3e68b9ab74eb54cfd186867f64f240e1a"), - ("GritLM-7B", "no_revision_available"), - ("GritLM-7B", "13f00a0e36500c80ce12870ea513846a066004af"), - ("Cohere-embed-multilingual-light-v3.0", "no_revision_available"), - ("bge-base-zh", "no_revision_available"), - ("voyage-code-2", "no_revision_available"), - ("sentence-t5-base", "no_revision_available"), - ("flaubert_large_cased", "no_revision_available"), - ("Cohere-embed-english-v3.0-instruct", "no_revision_available"), - ("SFR-Embedding-Mistral", "no_revision_available"), - ("dragon-plus", "no_revision_available"), - ("LLM2Vec-Sheared-Llama-unsupervised", "no_revision_available"), - ("text-embedding-3-small", "no_revision_available"), - ("flan-t5-base", "no_revision_available"), - ("text-search-ada-doc-001", "no_revision_available"), - ("bert-base-multilingual-cased", "no_revision_available"), - ("LLM2Vec-Meta-Llama-3-unsupervised", "no_revision_available"), - ("silver-retriever-base-v1", "no_revision_available"), - ("facebook-dpr-ctx_encoder-multiset-base", "no_revision_available"), + ("openai__text-search-davinci-001", "no_revision_available"), + ("McGill-NLP__LLM2Vec-Llama-2-unsupervised", "no_revision_available"), + ("openai__text-search-babbage-001", "no_revision_available"), + ("hkunlp__instructor-base", "no_revision_available"), + ("deepfile__embedder-100p", "no_revision_available"), + ("openai__text-embedding-ada-002-instruct", "no_revision_available"), + ("BAAI__bge-m3-instruct", "5617a9f61b028005a4858fdac845db406aefb181"), + ("FacebookAI__xlm-roberta-large", "no_revision_available"), + ("voyageai__voyage-2", "no_revision_available"), + ("openai__text-search-ada-001", "no_revision_available"), + ("sentence-transformers__gtr-t5-large", "no_revision_available"), + ("sentence-transformers__sentence-t5-xxl", "no_revision_available"), + ("openai__text-embedding-3-small-instruct", "no_revision_available"), + ("BAAI__bge-m3", "no_revision_available"), + ("voyageai__voyage-lite-02-instruct", "no_revision_available"), + ("openai__text-similarity-ada-001", "no_revision_available"), + ("McGill-NLP__LLM2Vec-Sheared-Llama-supervised", "no_revision_available"), + ("intfloat__e5-base", "no_revision_available"), + ("BAAI__bge-small-zh-v1.5", "no_revision_available"), + ("BAAI__bge-base-en", "no_revision_available"), + ("KBLab__electra-small-swedish-cased-discriminator", "no_revision_available"), + ("nomic-ai__nomic-embed-text-v1.5-512", "no_revision_available"), + ("McGill-NLP__LLM2Vec-Mistral-unsupervised", "no_revision_available"), + ("voyageai__voyage-law-2", "no_revision_available"), + ("dwzhu__e5-base-4k", "no_revision_available"), + ("T-Systems-onsite__cross-en-de-roberta-sentence-transformer", "no_revision_available"), + ("dangvantuan__sentence-camembert-base", "no_revision_available"), + ("Muennighoff__SGPT-5.8B-weightedmean-nli-bitfit", "no_revision_available"), + ("almanach__camembert-large", "no_revision_available"), + ("Muennighoff__SGPT-125M-weightedmean-msmarco-specb-bitfit-doc", "no_revision_available"), + ("baichuan-ai__text-embedding", "no_revision_available"), + ("sentence-transformers__LaBSE", "e34fab64a3011d2176c99545a93d5cbddc9a91b7"), + ("sentence-transformers__LaBSE", "no_revision_available"), + ("Wissam42__sentence-croissant-llm-base", "no_revision_available"), + ("Geotrend__bert-base-25lang-cased", "no_revision_available"), + ("bigscience-data__sgpt-bloom-7b1-msmarco", "no_revision_available"), + ("jonfd__electra-small-nordic", "no_revision_available"), + ("Muennighoff__SGPT-5.8B-weightedmean-msmarco-specb-bitfit", "no_revision_available"), + ("distilbert__distilbert-base-uncased", "no_revision_available"), + ("McGill-NLP__LLM2Vec-Meta-Llama-3-supervised", "no_revision_available"), + ("openai__text-embedding-3-large", "no_revision_available"), + ("Geotrend__bert-base-10lang-cased", "no_revision_available"), + ("sentence-transformers__sentence-t5-large", "no_revision_available"), + ("moka-ai__m3e-base", "no_revision_available"), + ("intfloat__e5-mistral-7b-instruct", "no_revision_available"), + ("almanach__camembert-base", "no_revision_available"), + ("vprelovac__universal-sentence-encoder-multilingual-3", "no_revision_available"), + ("dangvantuan__sentence-camembert-large", "no_revision_available"), + ("deepset__gelectra-large", "no_revision_available"), + ("intfloat__e5-large-v2", "no_revision_available"), + ("intfloat__e5-large-v2", "b322e09026e4ea05f42beadf4d661fb4e101d311"), + ("moka-ai__m3e-large", "no_revision_available"), + ("meta-llama__llama-2-7b-chat", "no_revision_available"), + ("bigscience-data__sgpt-bloom-1b7-nli", "no_revision_available"), + ("sentence-transformers__all-mpnet-base-v2", "84f2bcc00d77236f9e89c8a360a00fb1139bf47d"), + ("sentence-transformers__sentence-t5-xl", "no_revision_available"), + ("Geotrend__distilbert-base-en-fr-cased", "no_revision_available"), + ("openai__text-embedding-ada-002", "no_revision_available"), + ("BAAI__bge-small-en-v1.5-instruct", "5c38ec7c405ec4b44b94cc5a9bb96e735b38267a"), + ("shibing624__text2vec-base-multilingual", "no_revision_available"), + ("sentence-transformers__multi-qa-MiniLM-L6-cos-v1", "no_revision_available"), + ("jinaai__jina-embeddings-v2-base-en", "no_revision_available"), + ("mistralai__mistral-7b-instruct-v0.2", "no_revision_available"), + ("castorini__monot5-3b-msmarco-10k", "no_revision_available"), + ("Alibaba-NLP__gte-Qwen2-7B-instruct", "no_revision_available"), + ("google-bert__bert-base-multilingual-uncased", "no_revision_available"), + ("sentence-transformers__distiluse-base-multilingual-cased-v2", "no_revision_available"), + ("sentence-transformers__distiluse-base-multilingual-cased-v2", ".gitkeep"), + ("BAAI__bge-base-zh-v1.5", "no_revision_available"), + ("google-gecko__text-embedding-preview-0409", "no_revision_available"), + ("openai__text-search-curie-001", "no_revision_available"), + ("princeton-nlp__sup-simcse-bert-base-uncased", "no_revision_available"), + ("BAAI__bge-base-en-v1.5-instruct", "a5beb1e3e68b9ab74eb54cfd186867f64f240e1a"), + ("GritLM__GritLM-7B", "no_revision_available"), + ("GritLM__GritLM-7B", "13f00a0e36500c80ce12870ea513846a066004af"), + ("Cohere__Cohere-embed-multilingual-light-v3.0", "no_revision_available"), + ("BAAI__bge-base-zh", "no_revision_available"), + ("voyageai__voyage-code-2", "no_revision_available"), + ("sentence-transformers__sentence-t5-base", "no_revision_available"), + ("flaubert__flaubert_large_cased", "no_revision_available"), + ("Cohere__Cohere-embed-english-v3.0-instruct", "no_revision_available"), + ("Salesforce__SFR-Embedding-Mistral", "no_revision_available"), + ("facebookresearch__dragon-plus", "no_revision_available"), + ("McGill-NLP__LLM2Vec-Sheared-Llama-unsupervised", "no_revision_available"), + ("openai__text-embedding-3-small", "no_revision_available"), + ("google__flan-t5-base", "no_revision_available"), + ("openai__text-search-ada-doc-001", "no_revision_available"), + ("google-bert__bert-base-multilingual-cased", "no_revision_available"), + ("McGill-NLP__LLM2Vec-Meta-Llama-3-unsupervised", "no_revision_available"), + ("ipipan__silver-retriever-base-v1", "no_revision_available"), + ("facebook__dpr-ctx_encoder-multiset-base", "no_revision_available"), ("bm25s", "0_1_10"), - ("all-MiniLM-L12-v2", "a05860a77cef7b37e0048a7864658139bc18a854"), - ("dragon-plus-instruct", "no_revision_available"), - ("elser-v2", "no_revision_available"), - ("contriever-instruct", "2bd46a25019aeea091fd42d1f0fd4801675cf699"), - ("bge-small-en-v1.5", "5c38ec7c405ec4b44b94cc5a9bb96e735b38267a"), - ("SGPT-125M-weightedmean-msmarco-specb-bitfit", "no_revision_available"), - ("bge-large-zh-noinstruct", "no_revision_available"), - ("udever-bloom-560m", "no_revision_available"), - ("st-polish-paraphrase-from-distilroberta", "no_revision_available"), - ("gtr-t5-base", "no_revision_available"), - ("e5-mistral-7b-instruct-noinstruct", "07163b72af1488142a360786df853f237b1a3ca1"), - ("SGPT-2.7B-weightedmean-msmarco-specb-bitfit", "no_revision_available"), - ("xlm-roberta-base", "no_revision_available"), - ("bge-large-zh-v1.5", "no_revision_available"), - ("tart-dual-contriever-msmarco", "no_revision_available"), - ("text-embedding-preview-0409-768", "no_revision_available"), - ("DanskBERT", "no_revision_available"), - ("gbert-large", "no_revision_available"), - ("text-similarity-davinci-001", "no_revision_available"), - ("use-cmlm-multilingual", "no_revision_available"), - ("sentence-bert-swedish-cased", "no_revision_available"), - ("nomic-embed-text-v1", "no_revision_available"), - ("text-similarity-babbage-001", "no_revision_available"), - ("mistral-embed", "no_revision_available"), - ("voyage-large-2-instruct", "no_revision_available"), - ("flaubert_base_uncased", "no_revision_available"), - ("nomic-embed-text-v1.5-256", "no_revision_available"), - ("e5-large", "no_revision_available"), - ("bge-large-zh", "no_revision_available"), - ("distilbert-base-en-fr-es-pt-it-cased", "no_revision_available"), - ("SGPT-5.8B-weightedmean-msmarco-specb-bitfit-que", "no_revision_available"), - ("voyage-multilingual-2", "no_revision_available"), - ("all-mpnet-base-v2-instruct", "84f2bcc00d77236f9e89c8a360a00fb1139bf47d"), - ("SGPT-125M-weightedmean-msmarco-specb-bitfit-que", "no_revision_available"), - ("glove.6B.300d", "no_revision_available"), - ("OpenSearch-text-hybrid", "no_revision_available"), - ("gelectra-base", "no_revision_available"), - ("bge-small-zh", "no_revision_available"), - ("st-polish-paraphrase-from-mpnet", "no_revision_available"), + ("sentence-transformers__all-MiniLM-L12-v2", "a05860a77cef7b37e0048a7864658139bc18a854"), + ("facebookresearch__dragon-plus-instruct", "no_revision_available"), + ("elastic__elser-v2", "no_revision_available"), + ("facebook__contriever-instruct", "2bd46a25019aeea091fd42d1f0fd4801675cf699"), + ("BAAI__bge-small-en-v1.5", "5c38ec7c405ec4b44b94cc5a9bb96e735b38267a"), + ("Muennighoff__SGPT-125M-weightedmean-msmarco-specb-bitfit", "no_revision_available"), + ("BAAI__bge-large-zh-noinstruct", "no_revision_available"), + ("izhx__udever-bloom-560m", "no_revision_available"), + ("sdadas__st-polish-paraphrase-from-distilroberta", "no_revision_available"), + ("sentence-transformers__gtr-t5-base", "no_revision_available"), + ("intfloat__e5-mistral-7b-instruct-noinstruct", "07163b72af1488142a360786df853f237b1a3ca1"), + ("Muennighoff__SGPT-2.7B-weightedmean-msmarco-specb-bitfit", "no_revision_available"), + ("FacebookAI__xlm-roberta-base", "no_revision_available"), + ("BAAI__bge-large-zh-v1.5", "no_revision_available"), + ("orionweller__tart-dual-contriever-msmarco", "no_revision_available"), + ("openai__text-embedding-preview-0409-768", "no_revision_available"), + ("vesteinn__DanskBERT", "no_revision_available"), + ("deepset__gbert-large", "no_revision_available"), + ("openai__text-similarity-davinci-001", "no_revision_available"), + ("sentence-transformers__use-cmlm-multilingual", "no_revision_available"), + ("KBLab__sentence-bert-swedish-cased", "no_revision_available"), + ("nomic-ai__nomic-embed-text-v1", "no_revision_available"), + ("openai__text-similarity-babbage-001", "no_revision_available"), + ("mistral__mistral-embed", "no_revision_available"), + ("voyageai__voyage-large-2-instruct", "no_revision_available"), + ("flaubert__flaubert_base_uncased", "no_revision_available"), + ("nomic-ai__nomic-embed-text-v1.5-256", "no_revision_available"), + ("intfloat__e5-large", "no_revision_available"), + ("BAAI__bge-large-zh", "no_revision_available"), + ("Geotrend__distilbert-base-en-fr-es-pt-it-cased", "no_revision_available"), + ("Muennighoff__SGPT-5.8B-weightedmean-msmarco-specb-bitfit-que", "no_revision_available"), + ("voyageai__voyage-multilingual-2", "no_revision_available"), + ("sentence-transformers__all-mpnet-base-v2-instruct", "84f2bcc00d77236f9e89c8a360a00fb1139bf47d"), + ("Muennighoff__SGPT-125M-weightedmean-msmarco-specb-bitfit-que", "no_revision_available"), + ("sentence-transformers__average_word_embeddings_glove.6B.300d", "no_revision_available"), + ("aliyun__OpenSearch-text-hybrid", "no_revision_available"), + ("deepset__gelectra-base", "no_revision_available"), + ("BAAI__bge-small-zh", "no_revision_available"), + ("sdadas__st-polish-paraphrase-from-mpnet", "no_revision_available"), ("bm25", "no_revision_available"), - ("nomic-embed-text-v1.5-128", "no_revision_available"), - ("voyage-lite-01-instruct", "no_revision_available"), - ("instructor-large", "no_revision_available"), - ("contriever", "2bd46a25019aeea091fd42d1f0fd4801675cf699"), - ("gte-Qwen1.5-7B-instruct", "no_revision_available"), - ("msmarco-bert-co-condensor", "no_revision_available"), - ("text2vec-large-chinese", "no_revision_available"), - ("multilingual-e5-small", "e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), - ("multilingual-e5-small", "no_revision_available"), - ("monot5-3b-msmarco-10k", "no_revision_available"), - ("FollowIR-7B", "no_revision_available"), - ("herbert-base-retrieval-v2", "no_revision_available"), - ("udever-bloom-1b1", "no_revision_available"), - ("text-embedding-3-large-instruct", "no_revision_available"), - ("LLM2Vec-Llama-2-supervised", "no_revision_available"), - ("Cohere-embed-multilingual-v3.0", "no_revision_available"), - ("norbert3-large", "no_revision_available"), - ("tart-full-flan-t5-xl", "no_revision_available"), - ("nomic-embed-text-v1.5-64", "no_revision_available"), - ("nb-bert-base", "no_revision_available"), - ("distilbert-base-fr-cased", "no_revision_available"), - ("instructor-xl", "no_revision_available"), - ("text2vec-base-chinese", "no_revision_available"), - ("bge-large-en", "no_revision_available"), - ("bge-large-en-v1.5-instruct", "d4aa6901d3a41ba39fb536a557fa166f842b0e09"), - ("bert-base-uncased", "no_revision_available"), - ("all-MiniLM-L6-v2", "8b3219a92973c328a8e22fadcfa821b5dc75636a"), - ("all-MiniLM-L6-v2", "no_revision_available"), - ("e5-base-v2", "no_revision_available"), - ("e5-base-v2", "1c644c92ad3ba1efdad3f1451a637716616a20e8"), - ("gtr-t5-xl", "no_revision_available"), - ("norbert3-base", "no_revision_available"), - ("text-embedding-3-large-256", "no_revision_available"), - ("e5-small", "no_revision_available"), - ("komninos", "no_revision_available"), - ("monobert-large-msmarco", "no_revision_available"), - ("gottbert-base", "no_revision_available"), - ("nb-bert-large", "no_revision_available"), - ("unsup-simcse-bert-base-uncased", "no_revision_available"), - ("bert-base-15lang-cased", "no_revision_available"), - ("flaubert_base_cased", "no_revision_available"), - ("paraphrase-multilingual-MiniLM-L12-v2", "no_revision_available"), + ("nomic-ai__nomic-embed-text-v1.5-128", "no_revision_available"), + ("voyageai__voyage-lite-01-instruct", "no_revision_available"), + ("hkunlp__instructor-large", "no_revision_available"), + ("facebook__contriever", "2bd46a25019aeea091fd42d1f0fd4801675cf699"), + ("Alibaba-NLP__gte-Qwen1.5-7B-instruct", "no_revision_available"), + ("sentence-transformers__msmarco-bert-co-condensor", "no_revision_available"), + ("shibing624__text2vec-large-chinese", "no_revision_available"), + ("intfloat__multilingual-e5-small", "e4ce9877abf3edfe10b0d82785e83bdcb973e22e"), + ("intfloat__multilingual-e5-small", "no_revision_available"), + ("castorini__monot5-3b-msmarco-10k", "no_revision_available"), + ("castorini__monot5-base-msmarco-10k", "no_revision_available"), + ("jhu-clsp__FollowIR-7B", "no_revision_available"), + ("ipipan__herbert-base-retrieval-v2", "no_revision_available"), + ("izhx__udever-bloom-1b1", "no_revision_available"), + ("openai__text-embedding-3-large-instruct", "no_revision_available"), + ("McGill-NLP__LLM2Vec-Llama-2-supervised", "no_revision_available"), + ("McGill-NLP__LLM2Vec-Llama-2-7b-chat-hf-mntp-supervised", "no_revision_available"), + ("Cohere__Cohere-embed-multilingual-v3.0", "no_revision_available"), + ("ltg__norbert3-large", "no_revision_available"), + ("facebook__tart-full-flan-t5-xl", "no_revision_available"), + ("nomic-ai__nomic-embed-text-v1.5-64", "no_revision_available"), + ("NbAiLab__nb-bert-base", "no_revision_available"), + ("Geotrend__distilbert-base-fr-cased", "no_revision_available"), + ("hkunlp__instructor-xl", "no_revision_available"), + ("shibing624__text2vec-base-chinese", "no_revision_available"), + ("BAAI__bge-large-en", "no_revision_available"), + ("BAAI__bge-large-en-v1.5-instruct", "d4aa6901d3a41ba39fb536a557fa166f842b0e09"), + ("google-bert__bert-base-uncased", "no_revision_available"), + ("sentence-transformers__all-MiniLM-L6-v2", "8b3219a92973c328a8e22fadcfa821b5dc75636a"), + ("sentence-transformers__all-MiniLM-L6-v2", "no_revision_available"), + ("intfloat__e5-base-v2", "no_revision_available"), + ("intfloat__e5-base-v2", "1c644c92ad3ba1efdad3f1451a637716616a20e8"), + ("sentence-transformers__gtr-t5-xl", "no_revision_available"), + ("ltg__norbert3-base", "no_revision_available"), + ("openai__text-embedding-3-large-256", "no_revision_available"), + ("intfloat__e5-small", "no_revision_available"), + ("sentence-transformers__average_word_embeddings_komninos", "no_revision_available"), + ("castorini__monobert-large-msmarco", "no_revision_available"), + ("uklfr__gottbert-base", "no_revision_available"), + ("NbAiLab__nb-bert-large", "no_revision_available"), + ("princeton-nlp__unsup-simcse-bert-base-uncased", "no_revision_available"), + ("Geotrend__bert-base-15lang-cased", "no_revision_available"), + ("flaubert__flaubert_base_cased", "no_revision_available"), + ("sentence-transformers__paraphrase-multilingual-MiniLM-L12-v2", "no_revision_available"), ( - "paraphrase-multilingual-MiniLM-L12-v2", + "sentence-transformers__paraphrase-multilingual-MiniLM-L12-v2", "bf3bf13ab40c3157080a7ab344c831b9ad18b5eb", ), - ("all-MiniLM-L6-v2-instruct", "8b3219a92973c328a8e22fadcfa821b5dc75636a"), - ("distilbert-base-25lang-cased", "no_revision_available"), - ("LASER2", "no_revision_available"), - ("Cohere-embed-english-v3.0", "no_revision_available"), - ("SGPT-125M-weightedmean-nli-bitfit", "no_revision_available"), - ("titan-embed-text-v1", "no_revision_available"), - ("contriever-base-msmarco", "no_revision_available"), - ("bert-base-swedish-cased", "no_revision_available"), - ("multilingual-e5-large", "no_revision_available"), - ("multilingual-e5-large", "4dc6d853a804b9c8886ede6dda8a073b7dc08a81"), - ("text-similarity-curie-001", "no_revision_available"), - ("luotuo-bert-medium", "no_revision_available"), - ("facebookdragon-plus-context-encoder", "no_revision_available"), - ("bge-large-en-v1.5", "no_revision_available"), - ("bge-large-en-v1.5", "d4aa6901d3a41ba39fb536a557fa166f842b0e09"), - ("dfm-encoder-large-v1", "no_revision_available"), - ("GritLM-7B-noinstruct", "13f00a0e36500c80ce12870ea513846a066004af-temp"), - ("gtr-t5-xxl", "no_revision_available"), - ("google-gecko-256.text-embedding-preview-0409", "no_revision_available"), - ("multilingual-e5-base", "no_revision_available"), - ("multilingual-e5-base", "d13f1b27baf31030b7fd040960d60d909913633f"), + ("sentence-transformers__all-MiniLM-L6-v2-instruct", "8b3219a92973c328a8e22fadcfa821b5dc75636a"), + ("Geotrend__distilbert-base-25lang-cased", "no_revision_available"), + ("facebookresearch__LASER2", "no_revision_available"), + ("Cohere__Cohere-embed-english-v3.0", "no_revision_available"), + ("Muennighoff__SGPT-125M-weightedmean-nli-bitfit", "no_revision_available"), + ("amazon__titan-embed-text-v1", "no_revision_available"), + ("nthakur__contriever-base-msmarco", "no_revision_available"), + ("KB__bert-base-swedish-cased", "no_revision_available"), + ("intfloat__multilingual-e5-large", "no_revision_available"), + ("intfloat__multilingual-e5-large", "4dc6d853a804b9c8886ede6dda8a073b7dc08a81"), + ("openai__text-similarity-curie-001", "no_revision_available"), + ("silk-road__luotuo-bert-medium", "no_revision_available"), + ("facebook__dragon-plus-context-encoder", "no_revision_available"), + ("BAAI__bge-large-en-v1.5", "no_revision_available"), + ("BAAI__bge-large-en-v1.5", "d4aa6901d3a41ba39fb536a557fa166f842b0e09"), + ("chcaa__dfm-encoder-large-v1", "no_revision_available"), + ("GritLM__GritLM-7B-noinstruct", "13f00a0e36500c80ce12870ea513846a066004af-temp"), + ("sentence-transformers__gtr-t5-xxl", "no_revision_available"), + ("google-gecko__text-embedding-preview-0409-256", "no_revision_available"), + ("intfloat__-e5-base", "no_revision_available"), + ("intfloat__multilingual-e5-base", "d13f1b27baf31030b7fd040960d60d909913633f"), + ("intfloat__multilingual-e5-base", "no_revision_available"), ( - "paraphrase-multilingual-mpnet-base-v2", + "sentence-transformers__paraphrase-multilingual-mpnet-base-v2", "79f2382ceacceacdf38563d7c5d16b9ff8d725d6", ), - ("paraphrase-multilingual-mpnet-base-v2", "no_revision_available"), - ("flan-t5-large", "no_revision_available"), - ("rubert-tiny-turbo", "8ce0cf757446ce9bb2d5f5a4ac8103c7a1049054"), - ("SGPT-1.3B-weightedmean-msmarco-specb-bitfit", "no_revision_available"), - ("universal-sentence-encoder-multilingual-large-3", "no_revision_available"), - ("gbert-base", "no_revision_available"), - ("allenai-specter", "no_revision_available"), - ("LLM2Vec-Mistral-supervised", "no_revision_available"), + ("sentence-transformers__paraphrase-multilingual-mpnet-base-v2", "no_revision_available"), + ("google__flan-t5-large", "no_revision_available"), + ("sergeyzh__rubert-tiny-turbo", "8ce0cf757446ce9bb2d5f5a4ac8103c7a1049054"), + ("Muennighoff__SGPT-1.3B-weightedmean-msmarco-specb-bitfit", "no_revision_available"), + ("vprelovac__universal-sentence-encoder-multilingual-large-3", "no_revision_available"), + ("deepset__gbert-base", "no_revision_available"), + ("sentence-transformers__allenai-specter", "no_revision_available"), + ("McGill-NLP__LLM2Vec-Mistral-supervised", "no_revision_available"), ] diff --git a/tests/test_load_results.py b/tests/test_load_results.py index abfbd2c82a1446250ba28ebff2d7aaeb354c3817..994fc50d53aea86348054dbeb2ee332b9e6d48cd 100644 --- a/tests/test_load_results.py +++ b/tests/test_load_results.py @@ -23,4 +23,4 @@ def test_load_results(): known_model = "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2" known_revision = "bf3bf13ab40c3157080a7ab344c831b9ad18b5eb" assert known_model in results - assert known_revision in results[known_model] \ No newline at end of file + assert known_revision in results[known_model]