data.json

{"title": "Polish Information Retrieval Benchmark", "description": "Polish Information Retrieval Benchmark (PIRB) covers 41 Polish multidomain information retrieval tasks. Its purpose is to evaluate Polish and multilingual information retrieval methods on a wide range of problems with different characteristics, thus testing  the generalization ability of the models and their zero-shot performance. The benchmark includes pre-existing datasets such as MaupQA, BEIR-PL and PolEval-2022. We have also added new, previously unpublished datasets. The \"Web Datasets\" group contains real questions and answers from Polish web services.", "options": {"closeable": true, "showHelp": true}, "metrics": [{"id": "NDCG@10", "description": "Normalized Discounted Cumulative Gain at 10", "greaterIsBetter": true}, {"id": "MRR@10", "description": "Mean reciprocal rank at 10", "greaterIsBetter": true}, {"id": "Recall@100", "description": "Recall for the first 100 results", "greaterIsBetter": true}, {"id": "Accuracy@1", "description": "Is the first result relevant?", "greaterIsBetter": true}], "taskGroups": [{"id": "PolEval-2022", "description": "Tasks from the PolEval 2022 Passage Retrieval challenge. The evaluation includes all data splits except training.", "url": "https://beta.poleval.pl/challenge/2022-passage-retrieval"}, {"id": "Web Datasets", "description": "Question answering datasets crawled from various web sources."}, {"id": "BEIR-PL", "description": "Retrieval tasks from BEIR benchmark translated to Polish using Google Translate. Created by Wrocław University of Science and Technology.", "url": "https://arxiv.org/abs/2305.19840"}, {"id": "MaupQA", "description": "Massive Automatically-created Polish Question Answering Dataset, published by Piotr Rybak from IPI PAN.", "url": "https://aclanthology.org/2023.bsnlp-1.2/"}, {"id": "Other", "description": "Other datasets."}], "tasks": [{"id": "maupqa-1z10", "name": "1z10", "groupId": "MaupQA"}, {"id": "maupqa-czy-wiesz-v2", "name": "czy-wiesz-v2", "groupId": "MaupQA"}, {"id": "maupqa-gpt3-cc", "name": "gpt3-cc", "groupId": "MaupQA"}, {"id": "maupqa-gpt3.5-cc", "name": "gpt3.5-cc", "groupId": "MaupQA"}, {"id": "maupqa-gpt3.5-wiki", "name": "gpt3.5-wiki", "groupId": "MaupQA"}, {"id": "maupqa-mkqa", "name": "mkqa", "groupId": "MaupQA"}, {"id": "maupqa-mqa", "name": "mqa", "groupId": "MaupQA"}, {"id": "maupqa-multilingual-NLI", "name": "multilingual-NLI", "groupId": "MaupQA"}, {"id": "maupqa-poleval2021-pairs", "name": "poleval2021\npairs", "groupId": "MaupQA"}, {"id": "maupqa-poquad", "name": "poquad", "groupId": "MaupQA"}, {"id": "maupqa-templates", "name": "templates", "groupId": "MaupQA"}, {"id": "maupqa-wiki-def", "name": "wiki-def", "groupId": "MaupQA"}, {"id": "poleval-2022-dev-0-wiki-trivia", "name": "dev-0\n(wiki-trivia)", "groupId": "PolEval-2022"}, {"id": "poleval-2022-test-A-wiki-trivia", "name": "test-A\n(wiki-trivia)", "groupId": "PolEval-2022"}, {"id": "poleval-2022-test-A-legal-questions", "name": "test-A\n(legal-questions)", "groupId": "PolEval-2022"}, {"id": "poleval-2022-test-A-allegro-faq", "name": "test-A\n(allegro-faq)", "groupId": "PolEval-2022"}, {"id": "poleval-2022-test-B-wiki-trivia", "name": "test-B\n(wiki-trivia)", "groupId": "PolEval-2022"}, {"id": "poleval-2022-test-B-legal-questions", "name": "test-B\n(legal-questions)", "groupId": "PolEval-2022"}, {"id": "poleval-2022-test-B-allegro-faq", "name": "test-B\n(allegro-faq)", "groupId": "PolEval-2022"}, {"id": "arguana-pl", "name": "arguana", "groupId": "BEIR-PL"}, {"id": "dbpedia-pl", "name": "dbpedia", "groupId": "BEIR-PL"}, {"id": "fiqa-pl", "name": "fiqa", "groupId": "BEIR-PL"}, {"id": "hotpotqa-pl", "name": "hotpotqa", "groupId": "BEIR-PL"}, {"id": "msmarco-pl", "name": "msmarco", "groupId": "BEIR-PL"}, {"id": "nfcorpus-pl", "name": "nfcorpus", "groupId": "BEIR-PL"}, {"id": "nq-pl", "name": "nq", "groupId": "BEIR-PL"}, {"id": "quora-pl", "name": "quora", "groupId": "BEIR-PL"}, {"id": "scidocs-pl", "name": "scidocs", "groupId": "BEIR-PL"}, {"id": "scifact-pl", "name": "scifact", "groupId": "BEIR-PL"}, {"id": "trec-covid-pl", "name": "trec-covid", "groupId": "BEIR-PL"}, {"id": "gemini", "name": "gemini", "groupId": "Web Datasets"}, {"id": "odi", "name": "odi", "groupId": "Web Datasets"}, {"id": "onet", "name": "onet", "groupId": "Web Datasets"}, {"id": "zapytajfizyka", "name": "zapytajfizyka", "groupId": "Web Datasets"}, {"id": "techpedia", "name": "techpedia", "groupId": "Web Datasets"}, {"id": "pwn", "name": "pwn", "groupId": "Web Datasets"}, {"id": "eprawnik", "name": "eprawnik", "groupId": "Web Datasets"}, {"id": "specprawnik", "name": "specprawnik", "groupId": "Web Datasets"}, {"id": "abczdrowie", "name": "abczdrowie", "groupId": "Web Datasets"}, {"id": "mfaq", "name": "MFAQ", "groupId": "Other"}, {"id": "gpt-exams", "name": "GPT-exams", "groupId": "Other"}], "models": [{"id": "sparse", "name": "BM25", "description": "BM25 retrieval implementation based on pyserini", "url": "https://github.com/castorini/pyserini"}, {"id": "bm25", "name": "BM25", "description": "BM25 retrieval implementation based on pyserini", "url": "https://github.com/castorini/pyserini"}, {"id": "intfloat/multilingual-e5-small", "url": "https://huggingface.co/intfloat/multilingual-e5-small"}, {"id": "intfloat/multilingual-e5-base", "url": "https://huggingface.co/intfloat/multilingual-e5-base"}, {"id": "intfloat/multilingual-e5-large", "url": "https://huggingface.co/intfloat/multilingual-e5-large"}, {"id": "ipipan/herbert-base-retrieval-v1", "url": "https://huggingface.co/ipipan/herbert-base-retrieval-v1", "warning": "The model was trained on MaupQA datasets, so the results reported for them may be overestimated and unreliable. \nYou can use the ⮾ button to disable the results for a specific task group."}, {"id": "ipipan/herbert-base-retrieval-v2", "url": "https://huggingface.co/ipipan/herbert-base-retrieval-v2", "warning": "The model was trained on MaupQA datasets, so the results reported for them may be overestimated and unreliable. \nYou can use the ⮾ button to disable the results for a specific task group."}, {"id": "ipipan/silver-retriever-base-v1", "url": "https://huggingface.co/ipipan/silver-retriever-base-v1", "warning": "The model was trained on MaupQA datasets, so the results reported for them may be overestimated and unreliable. \nYou can use the ⮾ button to disable the results for a specific task group."}, {"id": "ipipan/herbert-base-qa-v1", "url": "https://huggingface.co/ipipan/herbert-base-qa-v1", "warning": "The model was trained on MaupQA datasets, so the results reported for them may be overestimated and unreliable."}, {"id": "./models/baseline-mnr", "name": "MNR baseline (base)", "description": "A baseline model (polish-roberta-base-v2) fine-tuned on MSMarco using MNR training script from Sentence-Transformers library.", "url": "https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/ms_marco/train_bi-encoder_mnrl.py"}, {"id": "./models/baseline-mnr-large", "name": "MNR baseline (large)", "description": "A baseline model (polish-roberta-large-v2) fine-tuned on MSMarco using MNR training script from Sentence-Transformers library.", "url": "https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/ms_marco/train_bi-encoder_mnrl.py"}, {"id": "./models/baseline-mse", "name": "MSE baseline (base)", "description": "A baseline model (polish-roberta-base-v2) fine-tuned on MSMarco using MSE training script from Sentence-Transformers library.", "url": "https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/ms_marco/train_bi-encoder_margin-mse.py"}, {"id": "./models/baseline-poleval2022-base", "name": "poleval-2022-base-model (mkozlowski)", "description": "A base model trained by Marek Kozłowski for his PolEval-2022 Passage Retrieval submission.", "url": "https://beta.poleval.pl/challenge/2022-passage-retrieval"}, {"id": "./models/mnr-large-v6-poleval2022", "name": "poleval-2022-large-model (mkozlowski)", "description": "A large model trained by Marek Kozłowski for his PolEval-2022 Passage Retrieval submission.", "url": "https://beta.poleval.pl/challenge/2022-passage-retrieval"}, {"id": "LaBSE", "warning": "The model was trained for bitext mining, so it's probably not suited for information retrieval.", "url": "https://huggingface.co/sentence-transformers/LaBSE"}, {"id": "distiluse-base-multilingual-cased-v2", "url": "https://huggingface.co/sentence-transformers/distiluse-base-multilingual-cased-v2"}, {"id": "paraphrase-multilingual-MiniLM-L12-v2", "warning": "The model was trained for semantic similarity, so it's probably not suited for information retrieval tasks.", "url": "https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2"}, {"id": "paraphrase-multilingual-mpnet-base-v2", "warning": "The model was trained for semantic similarity, so it's probably not suited for information retrieval tasks.", "url": "https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2"}, {"id": "xlm-r-bert-base-nli-stsb-mean-tokens", "warning": "The model was trained for semantic similarity, so it's probably not suited for information retrieval tasks.", "url": "https://huggingface.co/sentence-transformers/xlm-r-bert-base-nli-stsb-mean-tokens"}, {"id": "xlm-r-distilroberta-base-paraphrase-v1", "warning": "The model was trained for semantic similarity, so it's probably not suited for information retrieval tasks.", "url": "https://huggingface.co/sentence-transformers/xlm-r-distilroberta-base-paraphrase-v1"}, {"id": "Voicelab/sbert-base-cased-pl", "warning": "The model was trained for semantic similarity, so it's probably not suited for information retrieval tasks.", "url": "https://huggingface.co/Voicelab/sbert-base-cased-pl"}, {"id": "Voicelab/sbert-large-cased-pl", "warning": "The model was trained for semantic similarity, so it's probably not suited for information retrieval tasks.", "url": "https://huggingface.co/Voicelab/sbert-large-cased-pl"}, {"id": "radlab/polish-sts-v2", "warning": "The model was trained for semantic similarity, so it's probably not suited for information retrieval tasks.", "url": "https://huggingface.co/radlab/polish-sts-v2"}, {"id": "sdadas/st-polish-paraphrase-from-mpnet", "warning": "The model was trained for semantic similarity, so it's probably not suited for information retrieval tasks.", "url": "https://huggingface.co/sdadas/st-polish-paraphrase-from-mpnet"}, {"id": "sdadas/st-polish-paraphrase-from-distilroberta", "warning": "The model was trained for semantic similarity, so it's probably not suited for information retrieval tasks.", "url": "https://huggingface.co/sdadas/st-polish-paraphrase-from-distilroberta"}], "results": [{"id": "bm25", "results": {"gemini": {"Accuracy@1": 63.23529411764706, "Recall@100": 99.63235294117648, "MRR@10": 73.69149743230626, "NDCG@10": 78.3248260027549}, "odi": {"Accuracy@1": 63.36429308565531, "Recall@100": 91.22151784690482, "MRR@10": 71.01651186790505, "NDCG@10": 69.08801869530248}, "onet": {"Accuracy@1": 29.54400073106095, "Recall@100": 66.14273965091839, "MRR@10": 36.309632598356146, "NDCG@10": 39.89454435827909}, "zapytajfizyka": {"Accuracy@1": 59.47441217150761, "Recall@100": 96.61134163208852, "MRR@10": 67.77009374519757, "NDCG@10": 72.0657769671022}, "techpedia": {"Accuracy@1": 46.12710483432917, "Recall@100": 79.31558935361217, "MRR@10": 52.609227214333195, "NDCG@10": 55.80039285334023}, "pwn": {"Accuracy@1": 51.07736000493919, "Recall@100": 80.4655183058591, "MRR@10": 56.92787759050032, "NDCG@10": 59.719140350855724}, "eprawnik": {"Accuracy@1": 22.173139967772407, "Recall@100": 75.93209979441018, "MRR@10": 29.746880211958217, "NDCG@10": 34.10027937798345}, "specprawnik": {"Accuracy@1": 6.488824801730353, "Recall@100": 28.54130617639994, "MRR@10": 9.082821923530267, "NDCG@10": 9.701653702182611}, "abczdrowie": {"Accuracy@1": 4.59801200599413, "Recall@100": 19.68764246227726, "MRR@10": 6.286630794498378, "NDCG@10": 6.65195693264185}, "maupqa-1z10": {"Accuracy@1": 29.898348840961653, "Recall@100": 66.9149679987092, "MRR@10": 39.013084374644734, "NDCG@10": 42.31884377184016}, "maupqa-czy-wiesz-v2": {"Accuracy@1": 59.55017539032946, "Recall@100": 88.83348235779627, "MRR@10": 66.1626828552002, "NDCG@10": 69.39198712669831}, "maupqa-gpt3-cc": {"Accuracy@1": 15.345949142519219, "Recall@100": 20.89953347788948, "MRR@10": 16.421363176981156, "NDCG@10": 16.934937368256303}, 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"NDCG@10": 12.954749435400496}, "maupqa-templates": {"Accuracy@1": 49.602951291189896, "Recall@100": 82.24223097605203, "MRR@10": 57.19939973738495, "NDCG@10": 60.79906319013195}, "maupqa-wiki-def": {"Accuracy@1": 40.87216050406234, "Recall@100": 76.43840159177583, "MRR@10": 47.68992261323532, "NDCG@10": 51.186577602879844}, "poleval-2022-dev-0-wiki-trivia": {"Accuracy@1": 25.208681135225376, "Recall@100": 54.71897607122983, "MRR@10": 33.59077298142405, "NDCG@10": 25.18468017375704}, "poleval-2022-test-A-wiki-trivia": {"Accuracy@1": 25.75, "Recall@100": 53.17499999999995, "MRR@10": 35.20347222222221, "NDCG@10": 25.489746964669997}, "poleval-2022-test-A-legal-questions": {"Accuracy@1": 59.0, "Recall@100": 92.2309523809524, "MRR@10": 69.75595238095237, "NDCG@10": 67.70026204752939}, "poleval-2022-test-A-allegro-faq": {"Accuracy@1": 35.0, "Recall@100": 95.875, "MRR@10": 47.75962301587302, "NDCG@10": 53.830254572652635}, "poleval-2022-test-B-wiki-trivia": {"Accuracy@1": 24.354657687991022, "Recall@100": 55.46015712682378, "MRR@10": 34.526259063296074, "NDCG@10": 25.36562249148386}, "poleval-2022-test-B-legal-questions": {"Accuracy@1": 62.264150943396224, "Recall@100": 91.69436957172805, "MRR@10": 72.5399321154038, "NDCG@10": 69.37041014124561}, "poleval-2022-test-B-allegro-faq": {"Accuracy@1": 32.8, "Recall@100": 95.33333333333333, "MRR@10": 45.35563492063491, "NDCG@10": 51.59964301574148}, "arguana-pl": {"Accuracy@1": 13.584637268847795, "Recall@100": 84.42389758179232, "MRR@10": 24.065625776152068, "NDCG@10": 30.59458517868499}, "dbpedia-pl": {"Accuracy@1": 37.75, "Recall@100": 29.193820654595896, "MRR@10": 45.453174603174595, "NDCG@10": 22.856387940674527}, "fiqa-pl": {"Accuracy@1": 14.506172839506172, "Recall@100": 39.957874772689586, "MRR@10": 20.990961199294528, "NDCG@10": 16.716370256093544}, "hotpotqa-pl": {"Accuracy@1": 59.10871033085753, "Recall@100": 67.15732613099257, "MRR@10": 65.91778935296821, "NDCG@10": 49.72150145852755}, "msmarco-pl": {"Accuracy@1": 4.656160458452722, "Recall@100": 34.02698185291308, "MRR@10": 8.19231818802019, "NDCG@10": 10.16073202989729}, "nfcorpus-pl": {"Accuracy@1": 40.247678018575854, "Recall@100": 22.323695139880627, "MRR@10": 47.283527446066145, "NDCG@10": 41.11768996547916}, "nq-pl": {"Accuracy@1": 8.256083429895712, "Recall@100": 45.02462340672075, "MRR@10": 13.608639574021959, "NDCG@10": 15.73609597077902}, "quora-pl": {"Accuracy@1": 54.02, "Recall@100": 85.4804831513749, "MRR@10": 61.590456349206086, "NDCG@10": 61.93112317770259}, "scidocs-pl": {"Accuracy@1": 15.4, "Recall@100": 29.214999999999915, "MRR@10": 22.24424603174603, "NDCG@10": 11.941969126664839}, "scifact-pl": {"Accuracy@1": 50.0, "Recall@100": 85.54444444444445, "MRR@10": 58.279365079365064, "NDCG@10": 61.48938134190038}, "trec-covid-pl": {"Accuracy@1": 52.0, "Recall@100": 7.678545268503495, "MRR@10": 63.07460317460317, "NDCG@10": 43.618059032296294}, "mfaq": {"Accuracy@1": 38.45179473375873, "Recall@100": 71.751349810789, "MRR@10": 45.80429697621635, "NDCG@10": 49.46027356710991}, "gpt-exams": {"Accuracy@1": 85.56143155823392, "Recall@100": 99.85241667691551, "MRR@10": 90.70177724678989, "NDCG@10": 92.71649692518264}}}, {"id": "sdadas/st-polish-paraphrase-from-mpnet", "results": {"gemini": {"Accuracy@1": 85.66176470588235, "Recall@100": 100.0, "MRR@10": 90.61172385620917, "NDCG@10": 92.56819485002434}, "odi": {"Accuracy@1": 76.78018575851394, "Recall@100": 98.95080839353285, "MRR@10": 83.22415515913973, "NDCG@10": 82.67506641880368}, "onet": {"Accuracy@1": 29.0505345883213, "Recall@100": 73.48990222059764, "MRR@10": 37.06467423546853, "NDCG@10": 41.15581360167101}, "zapytajfizyka": {"Accuracy@1": 63.48547717842324, "Recall@100": 99.37759336099586, "MRR@10": 73.19019078355184, "NDCG@10": 77.70049500974969}, "techpedia": {"Accuracy@1": 56.46931015752308, "Recall@100": 92.43889190657252, "MRR@10": 64.60251071277663, "NDCG@10": 68.41551926039004}, "pwn": {"Accuracy@1": 46.7802679508551, "Recall@100": 81.7558807186516, "MRR@10": 53.639829931272644, "NDCG@10": 57.0651038997884}, "eprawnik": {"Accuracy@1": 23.2955492582097, "Recall@100": 79.27432349836083, "MRR@10": 31.606193624863984, "NDCG@10": 36.35399616585628}, "specprawnik": {"Accuracy@1": 7.361211247296323, "Recall@100": 37.001682287911564, "MRR@10": 10.636861846396775, "NDCG@10": 11.579204982054609}, "abczdrowie": {"Accuracy@1": 6.629897940182839, "Recall@100": 31.23674656588074, "MRR@10": 9.399124462646151, "NDCG@10": 10.084203677470095}, "maupqa-1z10": {"Accuracy@1": 20.54536653579304, "Recall@100": 54.827085462270745, "MRR@10": 27.273613384111865, "NDCG@10": 29.096921582099274}, "maupqa-czy-wiesz-v2": {"Accuracy@1": 37.70892083361992, "Recall@100": 77.3643304216246, "MRR@10": 44.73034350957613, "NDCG@10": 48.497155339078624}, "maupqa-gpt3-cc": {"Accuracy@1": 9.481569091267495, "Recall@100": 19.394835403114527, "MRR@10": 11.144637498865775, "NDCG@10": 12.010439402488858}, "maupqa-gpt3.5-cc": {"Accuracy@1": 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