dataset: add human tasks and benchmark by Samoed · Pull Request #3214 · embeddings-benchmark/mteb

Samoed · 2025-09-25T16:06:00Z

Cherry-picked commits from #3213 from @AdnanElAssadi56

mteb/tasks/Classification/eng/human/__init__.py

mteb/tasks/Classification/eng/HUMEEmotionClassification.py

mteb/tasks/Classification/multilingual/MultilingualSentimentClassificationHumanSubset.py

mteb/tasks/Reranking/eng/human/Robust04InstructionRerankingHumanSubset.py

mteb/tasks/STS/multilingual/HUMESTS22.py

mteb/tasks/Classification/eng/EmotionClassificationHumanSubset.py

mteb/tasks/Classification/eng/HUMEEmotionClassification.py

isaac-chung · 2025-09-27T18:09:42Z

I'll add a benchmark object as well

KennethEnevoldsen

Looks good - a few minor changes

should we add it to the leaderboard as well
should we add a "human" model (otherwise the scores won't appear on the leaderboard). Should probably be filtered out by default.
and 2) are probably for another PR

mteb/benchmarks/benchmarks/benchmarks.py

mteb/tasks/Classification/eng/EmotionClassificationHumanSubset.py

Samoed · 2025-09-29T08:59:16Z

should we add a "human" model (otherwise the scores won't appear on the leaderboard). Should probably be filtered out by default.

Yes, I wanted to do like this

should we add it to the leaderboard as well

I will add after adding "human" model

Co-authored-by: Kenneth Enevoldsen <kennethcenevoldsen@gmail.com>

Samoed · 2025-09-29T10:34:39Z

mteb/tasks/Classification/eng/ToxicConversationsClassificationHumanSubset.py

+        # Combine: subsampled train + human test
+        self.dataset = DatasetDict(
+            {
+                "train": original_with_train["test"],  # This becomes our training data


@AdnanElAssadi56 Why do we use test split from original dataset as train?

tests/test_tasks/test_all_abstasks.py

tests/test_TaskMetadata.py

mteb/load_results/load_results.py

mteb/benchmarks/benchmarks/benchmarks.py

mteb/leaderboard/benchmark_selector.py

AdnanElAssadi56

Looks good to me! I guess we'll stick with results from here and update paper.

isaac-chung · 2025-10-02T04:44:14Z

@AdnanElAssadi56 results on the LB are aggregated differently. Instead, we can explore a custom aggregation (needed in MIEB as well), as @Samoed suggested.

Samoed · 2025-10-02T05:18:48Z

We can merge this, but without adding to the leaderboard

isaac-chung · 2025-10-02T05:40:07Z

We can merge this, but without adding to the leaderboard

Yeah. Let's do that in a separate PR.

Co-authored-by: Roman Solomatin <samoed.roman@gmail.com>

* fix: Correct metadata for ArguAna dataset (#3202) * Update tasks & benchmarks tables * 1.38.57 Automatically generated by python-semantic-release * model: Add BMRetriever (#3195) * model: Add BMRetriever * Update mteb/models/bmretriever_models.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Update mteb/models/bmretriever_models.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * fix: remove trust_remote_code option * feat: implement BMREtrieverWrapper based on InstructSentenceTransformerWrapper * refactor: update training datasets for bmretriever --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Revert "Ci: test out GH models with welcoming new comers" (#3206) Revert "Ci: test out GH models with welcoming new comers (#3112)" This reverts commit 73a35e0. * model: Add Codefuse models (#3205) * add codefuse models * add codefuse models * Update codefuse_models.py * lint codefuse.py * fix(models): ensure prompt_type is passed to format_instruction (#3216) * 1.38.58 Automatically generated by python-semantic-release * Adding Cohere's output_dimension and embedding_type parameter (#3204) * Adding Cohere's output_dimension and embedding_type parameter Cohere's embed-v4 binary and int8 * Correcting due to comments * dataset: add swedish cpc patent classifications to mteb (#3072) * feat: add swedish cpc patent classifications to mteb * fix: formatting and init imports * fix: update mteb task according to feedback * fix: perform citation and code formatting * fix: add train and test split for both datasets * fix: AttributeError in ColPaliEngineWrapper similarity method (#3177) * fix: delete kwargs for similarity score in ColPaliEngineWrapper for method behavior * chore: fix colpali_models similarity handle device * Update tasks & benchmarks tables * 1.38.59 Automatically generated by python-semantic-release * fix: prevent EOS token truncation (#3218) * fix(models): prevent EOS token truncation for BMRetriever * refactor(models): refactor tokenizer setup in `InstructSentenceTransformerWrapper` * fix(models): correct eos token handling in `BMRetrieverWrapper` * 1.38.60 Automatically generated by python-semantic-release * Update giga embeddings (#3210) * update giga embeddings * update giga embeddings * 3b-september-2025 * fixed * lint * Update mteb/models/ru_sentence_models.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * change revision due to flash-attn dependency * change apply_instruction_to_passages --------- Co-authored-by: Kolodin Egor <eikolodin@sberbank.ru> Co-authored-by: Roman Solomatin <36135455+Samoed@users.noreply.github.com> Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> Co-authored-by: Неизвестный Пользователь722497 <dolegosmirnov@sberbank.ru> * fix: Refactor split create_tables into static Benchmark methods (#3126) * feat - Split create_tables into static Benchmark methods * feat - format * Update mteb/leaderboard/table.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * feat - remove search query;take benchmark result as input;addressing the circular import, * feat - format * Update mteb/benchmarks/benchmark.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/benchmarks/benchmark.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * feat - use to_dataframe;clean table.py;move creat_table * feat - fix circular import * feat - clean-up * feat - format --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * 1.38.61 Automatically generated by python-semantic-release * Extending the RTEB benchmark (#3223) Adding another voyageai model * Update tasks & benchmarks tables * model: New qzmodel (#3211) * Update qzhou_models.py * Update qzhou_models.py * reformat script code * Update configuration * According to our new decision, the model name has been changed to "QZhou-Embedding-Zh". * Fix variable naming issues. * model: Update Youtu embedding model (#3227) * add youtu models * add a blank line * fix the optional dependencies and lint the code * remove unused dependencies and reformat * revise prompt_type * update youtu_models --------- Co-authored-by: springxchen <springxchen@tencent.com> * dataset: Add Software Issue Localization Datasets (#3178) * add software issue localization datasets * add software issue localization datasets * update and add multilingual datasets * fix citation format issues * Update mteb/tasks/Reranking/eng/SWEbenchVerifiedReranking.py * fix linting issues --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Update tasks & benchmarks tables * feat: Officially include RTEB in the leaderboard (#3222) * feat - adjust Rteb's Benchmark * feat - add blank * fix menu names * Update mteb/leaderboard/benchmark_selector.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * moving around tasks * fix: Update RTEB summary columns (#3226) * fix(models): ensure prompt_type is passed to format_instruction (#3216) * 1.38.58 Automatically generated by python-semantic-release * Adding Cohere's output_dimension and embedding_type parameter (#3204) * Adding Cohere's output_dimension and embedding_type parameter Cohere's embed-v4 binary and int8 * Correcting due to comments * dataset: add swedish cpc patent classifications to mteb (#3072) * feat: add swedish cpc patent classifications to mteb * fix: formatting and init imports * fix: update mteb task according to feedback * fix: perform citation and code formatting * fix: add train and test split for both datasets * fix: AttributeError in ColPaliEngineWrapper similarity method (#3177) * fix: delete kwargs for similarity score in ColPaliEngineWrapper for method behavior * chore: fix colpali_models similarity handle device * Update tasks & benchmarks tables * 1.38.59 Automatically generated by python-semantic-release * fix: prevent EOS token truncation (#3218) * fix(models): prevent EOS token truncation for BMRetriever * refactor(models): refactor tokenizer setup in `InstructSentenceTransformerWrapper` * fix(models): correct eos token handling in `BMRetrieverWrapper` * 1.38.60 Automatically generated by python-semantic-release * Update giga embeddings (#3210) * update giga embeddings * update giga embeddings * 3b-september-2025 * fixed * lint * Update mteb/models/ru_sentence_models.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * change revision due to flash-attn dependency * change apply_instruction_to_passages --------- Co-authored-by: Kolodin Egor <eikolodin@sberbank.ru> Co-authored-by: Roman Solomatin <36135455+Samoed@users.noreply.github.com> Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> Co-authored-by: Неизвестный Пользователь722497 <dolegosmirnov@sberbank.ru> * fix: Refactor split create_tables into static Benchmark methods (#3126) * feat - Split create_tables into static Benchmark methods * feat - format * Update mteb/leaderboard/table.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * feat - remove search query;take benchmark result as input;addressing the circular import, * feat - format * Update mteb/benchmarks/benchmark.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/benchmarks/benchmark.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * feat - use to_dataframe;clean table.py;move creat_table * feat - fix circular import * feat - clean-up * feat - format --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * 1.38.61 Automatically generated by python-semantic-release * Extending the RTEB benchmark (#3223) Adding another voyageai model * Update tasks & benchmarks tables * feat - filter_by_privacy * feat - add new fields for rteb part * feat - getattr * feat - adjust privacy filter logic * feat - enhance summary table column renaming and add 'is_public' field mapping * fix: remove unused 'is_public' attribute from TaskResult --------- Co-authored-by: Yongbin Choi <whybe.choi@gmail.com> Co-authored-by: semantic-release <semantic-release> Co-authored-by: fzoll <5575946+fzoll@users.noreply.github.com> Co-authored-by: Atheer <atheer2104@protonmail.com> Co-authored-by: Yong woo Song <ywsong.dev@kakao.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Egor <31567312+ekolodin@users.noreply.github.com> Co-authored-by: Kolodin Egor <eikolodin@sberbank.ru> Co-authored-by: Roman Solomatin <36135455+Samoed@users.noreply.github.com> Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> Co-authored-by: Неизвестный Пользователь722497 <dolegosmirnov@sberbank.ru> Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> Co-authored-by: smile <smile@pinai.io> Co-authored-by: ethan <smiletoye@gmail.com> * removed show_rteb args * avoid defining function where we can just use the metadata * minor fixes * minor fixes * fix: Correct logic for filtering public tasks in ModelResult class (#3230) Co-authored-by: ethan <smiletoye@gmail.com> --------- Co-authored-by: q275343119 <275343119@qq.com> Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> Co-authored-by: 笑尿伊人 <44760272+q275343119@users.noreply.github.com> Co-authored-by: Yongbin Choi <whybe.choi@gmail.com> Co-authored-by: fzoll <5575946+fzoll@users.noreply.github.com> Co-authored-by: Atheer <atheer2104@protonmail.com> Co-authored-by: Yong woo Song <ywsong.dev@kakao.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Egor <31567312+ekolodin@users.noreply.github.com> Co-authored-by: Kolodin Egor <eikolodin@sberbank.ru> Co-authored-by: Roman Solomatin <36135455+Samoed@users.noreply.github.com> Co-authored-by: Неизвестный Пользователь722497 <dolegosmirnov@sberbank.ru> Co-authored-by: smile <smile@pinai.io> Co-authored-by: ethan <smiletoye@gmail.com> * Update tasks & benchmarks tables * 1.39.0 Automatically generated by python-semantic-release * fix: Add submission references for RTEB (#3233) * fix: Add rteb submission references and improve descriptions. * Added evaluation request * added field for tasks * 1.39.1 Automatically generated by python-semantic-release * dataset: add human tasks and benchmark (#3214) * Human Subsets Tasks * Fixed Multilingual Classification Subset * linting * fix citations format * make lint * fix tests * remove human folder * fix relative imports * add adapted_from for all human subsets * fix pydantic errors * add benchmark object * make benchmark discoverable * bibtex test * Apply suggestion Co-authored-by: Kenneth Enevoldsen <kennethcenevoldsen@gmail.com> * Apply suggestions from code review Co-authored-by: Kenneth Enevoldsen <kennethcenevoldsen@gmail.com> * rename & reupload * upd tests * upd tests again * add model * add benchmark to leaderboard * change branch of leaderboard * remove branch of load data * fix model meta path * make mteb importable * update repo * Update mteb/benchmarks/benchmarks/benchmarks.py * Update mteb/leaderboard/benchmark_selector.py * Update mteb/load_results/load_results.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> --------- Co-authored-by: Adnan El Assadi <aassadi22@ku.edu.tr> Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> Co-authored-by: Kenneth Enevoldsen <kennethcenevoldsen@gmail.com> Co-authored-by: AdnanElAssadi56 <115242814+AdnanElAssadi56@users.noreply.github.com> * Update tasks & benchmarks tables * Remove 'HUME(v1)' from leaderboard benchmark (#3236) * Remove 'HUME(v1)' from leaderboard benchmark * lint * docs: Update adding benchmark documentation (#3229) * update adding_a_benchmark.md documentation * fix numbers * fix: Further specified macro-language code for Norwegian (#3228) * fix: Further specified macro-language code for Norwegian "nor" is a macro-language code that covers bokmål and nynorsk (both norwegian), but this means that these datasets will be missed if using "nob" or "nno". Specifying it like this should allow this. * furhter specified macro language "nor" * Update tasks & benchmarks tables * 1.39.2 Automatically generated by python-semantic-release * fix max tokens (#3243) * fix models * fix imports * fix task import * reupload HUME tasks * reupload SWE tasks * add stats * fix python39 transformers compatibility (#3254) * fix python39 transformers * fix * Aggregate by subset for HUMEv1 (#3255) aggregate by subset for HUMEv1 * Update tasks & benchmarks tables * Fix AbsTaskTextRegression task (#3257) Fix AbsTaskTextRegression * Added Japanese to Retrieval (#3252) * feat - add Japanese * feat - use mteb.get_benchmark * fix - 3.9 test error * Revert "fix - 3.9 test error" This reverts commit 6bfee53. * fix - 3.9 test error * Update tasks & benchmarks tables * fix bm25 on small datasets (#3261) --------- Co-authored-by: Yongbin Choi <whybe.choi@gmail.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: semantic-release <semantic-release> Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> Co-authored-by: Geralt <94539084+Geralt-Targaryen@users.noreply.github.com> Co-authored-by: fzoll <5575946+fzoll@users.noreply.github.com> Co-authored-by: Atheer <atheer2104@protonmail.com> Co-authored-by: Yong woo Song <ywsong.dev@kakao.com> Co-authored-by: Egor <31567312+ekolodin@users.noreply.github.com> Co-authored-by: Kolodin Egor <eikolodin@sberbank.ru> Co-authored-by: Неизвестный Пользователь722497 <dolegosmirnov@sberbank.ru> Co-authored-by: 笑尿伊人 <44760272+q275343119@users.noreply.github.com> Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> Co-authored-by: Peter <51702222+PennyYu123@users.noreply.github.com> Co-authored-by: spring-quan <38248619+spring-quan@users.noreply.github.com> Co-authored-by: springxchen <springxchen@tencent.com> Co-authored-by: Tarun Suresh <68882529+tarsur909@users.noreply.github.com> Co-authored-by: Kenneth Enevoldsen <kennethcenevoldsen@gmail.com> Co-authored-by: q275343119 <275343119@qq.com> Co-authored-by: smile <smile@pinai.io> Co-authored-by: ethan <smiletoye@gmail.com> Co-authored-by: Adnan El Assadi <aassadi22@ku.edu.tr> Co-authored-by: AdnanElAssadi56 <115242814+AdnanElAssadi56@users.noreply.github.com> Co-authored-by: Niklas <n.muennighoff@gmail.com> Co-authored-by: Alexey Vatolin <vatolinalex@gmail.com>

* model: add image support for jina embeddings v4 (#2893) * feat: unify text and image embeddings for all tasks * fix: uniform batch size * fix: update error message * fix: update code task * fix: update max length * fix: apply review suggestions * model: add kalm_models (kalm-emb-v2) ModelMeta (new PR) (#2889) * feat: add KaLM_Embedding_X_0605 in kalm_models * Update kalm_models.py for lint format * kalm-emb-v2 * kalm-emb-v2 * kalm-emb-v2 * kalm-emb-v2 * kalm-emb-v2 --------- Co-authored-by: xinshuohu <xinshuohu@tencent.com> Co-authored-by: Xinshuo Hu <yanshek.woo@gmail.com> * Add Classification Evaluator unit test (#2838) * Adding Classification Evaluator test * Modifications due to the comments * Update tests/test_evaluators/test_ClassificationEvaluator.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update tests/test_evaluators/test_ClassificationEvaluator.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Modifications due to the comments * Modifications due to the comments --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * fix: update colpali engine models (#2905) * adding vidore benchmarks * fix typo * clean vidore names + per lang eval * lint * vidore names * bibtex fix * fix revision * vidore v2 citation * update citation format and fix per-language mappings * lint: citations * typo citations * fix revisiions * lint * fix colnomic3b revision * fix colqwen2.5 revision + latest repo version * fix query agmentation tokens * colsmol revision * 1.38.35 Automatically generated by python-semantic-release * Evaluator tests (#2910) * Adding Classification Evaluator test * Modifications due to the comments * Update tests/test_evaluators/test_ClassificationEvaluator.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update tests/test_evaluators/test_ClassificationEvaluator.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Modifications due to the comments * Modifications due to the comments * Adding STSEvaluator and SummarizationEvaluator tests * Correcting due to the comments * Correcting due to the comments --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Classification dataset cleaning (#2900) * Classification dataset cleaning * Update pull request number * Fix metadata test * fix formatting * add script for cleaning * Update tasks & benchmarks tables * dataset: Add JapaneseSentimentClassification (#2913) Add JapaneseSentimentClassification * Update tasks & benchmarks tables * fix: change `passage` prompt to `document` (#2912) * change document to passage * fix prompt names * fix kwargs check * fix default prompt * 1.38.36 Automatically generated by python-semantic-release * model: Add OpenSearch inf-free sparse encoding models (#2903) add opensearch inf-free models Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> * dataset: add BarExamQA dataset (#2916) * Add BareExamQA retrieval task * ran linter * updated details * updated details * fixed subtype name * fixed changes * ran linter again * Use `mteb.get_model` in adding_a_dataset.md (#2922) Update adding_a_dataset.md * fix: specify revision for opensearch (#2919) specify revision for opensearch * 1.38.37 Automatically generated by python-semantic-release * Update the link for gemini-embedding-001 (#2928) * fix: replace with passage (#2934) * fix: Only import SparseEncoder once sentence-transformer version have been checked (#2940) * fix: Only import SparseEncoder once sentence-transformer version have been checked fixes #2936 * Update mteb/models/opensearch_neural_sparse_models.py Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> --------- Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> * fix: Prevent incorrectly passing "selector_state" to `get_benchmark` (#2939) The leaderboard would have (silent) errors where `get_benchmark` lead to a KeyError due to "selector_state" being passed as a default value. Setting `DEFAULT_BENCMARK_NAME` as the value solves this issue. * docs: Update adding_a_dataset.md (#2947) * docs: Update adding_a_dataset.md * Update docs/adding_a_dataset.md * ci: bump semantic release * 1.38.38 Automatically generated by python-semantic-release * dataset: Add BSARD v2, fixing the data loading issues of v1 (#2935) * BSARD loader fixed * BSARDv2 metadata fixed * Update mteb/tasks/Retrieval/fra/BSARDRetrieval.py --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update tasks & benchmarks tables * dataset: add GovReport dataset (#2953) * Added govreport task * Updated description * dataset: add BillSum datasets (#2943) * Added BillSum datasets * fixed billsumca * Updated BillSumCA description * Updated BillSumUS description * Update mteb/tasks/Retrieval/eng/BillSumCA.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/tasks/Retrieval/eng/BillSumUS.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * lint * lint --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> * Update tasks & benchmarks tables * fix: Add new benchmark beRuSciBench along with AbsTaskTextRegression (#2716) * Add RuSciBench * fix bitext mining lang * Add regression task * fix init * add missing files * Improve description * Add superseded_by * fix lint * Update regression task to match with v2 * Add stratified_subsampling for regression task * Add boostrap for regression task * Rename task class, add model as evaluator argument * fix import * fix import 2 * fixes * fix * Rename regression model protocol * Update tasks & benchmarks tables * 1.38.39 Automatically generated by python-semantic-release * qzhou-embedding model_meta & implementation (#2975) * qzhou-embedding model_meta & implementation * Update qzhou_models.py * Update qzhou_models.py Processing todo items（Add default instruction） * Update qzhou_models.py correct bge datalist * Update qzhou_models.py correct 'public_training_data' * Update qzhou_models.py * Update qzhou_models.py * Update qzhou_models.py * Update qzhou_models.py * Update mteb/models/qzhou_models.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Update mteb/models/qzhou_models.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * format qzhou_models.py for ruff check --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * model: Add Voyage 3.5 model configuration (#3005) Add Voyage 3.5 model configuration - Add voyage_3_5 ModelMeta with 1024 embed dimensions and 32000 max tokens - Set release date to 2025-01-21 with revision 1 - Configure for cosine similarity with instruction support - Include standard Voyage training datasets reference 🤖 Generated with [Claude Code](https://claude.ai/code) Co-authored-by: Claude <noreply@anthropic.com> * model: BAAI/bge-m3-unsupervised Model (#3007) * Add BAAI/bge-m3-unsupervised Model (BAAI/bge_m3_retromae is commented out - the details are proper, but it fails during loading the model for me, so i commented out) * Remove the commented retromae model --------- Co-authored-by: fzowl <zoltan@voyageai.com> * lint: Correcting lint errors (#3004) * Adding Classification Evaluator test * Modifications due to the comments * Update tests/test_evaluators/test_ClassificationEvaluator.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update tests/test_evaluators/test_ClassificationEvaluator.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Modifications due to the comments * Modifications due to the comments * Correcting the lint errors --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * dataset: Added 50 Vietnamese dataset from vn-mteb (#2964) * [ADD] 50 vietnamese dataset from vn-mteb * [UPDATE] task metadata * [UPDATE] import dependencies * [UPDATE] task metadata, bibtext citation * [UPDATE-TEST] test_model_meta * [UPDATE] sample_creation to machine-translated and LM verified * [ADD] sample creation machine-translated and LM verified * [REMOVE] default fields metadata in Classfication tasks * Update tasks & benchmarks tables * model: Add Cohere embed-v4.0 model support (#3006) * Add Cohere embed-v4.0 model support - Add text-only embed-v4.0 model in cohere_models.py - Add multimodal embed-v4.0 model in cohere_v.py - Support configurable dimensions (256, 512, 1024, 1536) - Support 128,000 token context length - Support multimodal embedding (text, images, mixed PDFs) 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> * Add Cohere embed-v4.0 model support Update cohere_v.py and cohere_models.py to include the new embed-v4.0 model with proper configuration and integration. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: Claude <noreply@anthropic.com> * Add OpenAI models with 512 dimension (#3008) * Add OpenAI/text-embedding-3-small (512 dim) Add OpenAI/text-embedding-3-large (512 dim) * Correcting due to comments --------- Co-authored-by: fzowl <zoltan@voyageai.com> * Standardise task names and fix citation formatting (#3026) fixes for name formatting * Update tasks & benchmarks tables * fix: Add missing training sets for qzhou (#3023) * Supplement missing training sets * reformat code * Reorganize the data list format * update qzhou_model meta * 1.38.40 Automatically generated by python-semantic-release * model: Add samilpwc_models meta (#3028) * model: Add samilpwc_models meta * Fix: Remove CONST * Fix: Reformat File * Update: model revision * model: Add granite-vision-embedding model (#3029) * Add files via upload * Address review comments * Address review comments * ruff format * Update mteb/models/granite_vision_embedding_models.py * lint error fix --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * fix: incorrect revision for SNLRetrieval (#3033) The provided revisions doesn't seem to be present on: adrlau/navjordj-SNL_summarization_copy Replacing with latest revision * dataset: Add HumanEvalRetrieval task (#3022) * Add HumanEvalRetrieval dataset * Fix TaskMetadata structure and remove descriptive_stats - Use TaskMetadata class instead of dict - Remove descriptive_stats as requested in PR review - Add date field and proper import structure * Fix dataset path and use verified metadata - Change path from zeroshot/humaneval-embedding-benchmark to embedding-benchmark/HumanEval - Use actual description from HuggingFace dataset page - Remove fabricated citation and reference - Remove revision field that was incorrect - Reference HuggingFace dataset page instead of arxiv * Add correct revision hash to HumanEval - Add revision hash: ed1f48a for reproducibility * Fix HumanEval metadata validation - Add date field for metadata completeness - Add bibtex_citation field (empty string) - Required for TaskMetadata validation to pass - Should resolve PR test failure * Address reviewer feedback - Remove trust_remote_code parameter as requested - Add revision parameter to load_dataset() calls for consistency - Use metadata revision hash in dataset loading for reproducibility * Fix field names in HumanEval dataset loading Changed query_id/corpus_id to query-id/corpus-id to match actual dataset format. * Fix deprecated metadata_dict usage Use self.metadata.dataset instead of self.metadata_dict for v2.0 compatibility. * Fix data structure for MTEB compatibility - Organize data by splits as expected by MTEB retrieval tasks - Convert scores to integers for pytrec_eval compatibility * Address PR feedback for HumanEval dataset - Add descriptive statistics using calculate_metadata_metrics() - Enhance metadata description with dataset structure details - Add complete BibTeX citation for original paper - Update to full commit hash revision - Add python-Code language tag for programming language - Explain retrieval task formulation clearly * Fix BibTeX citation formatting for HumanEvalRetrieval - Update citation to match bibtexparser formatting requirements - Fields now in alphabetical order with lowercase names - Proper trailing commas and indentation * Update tasks & benchmarks tables * 1.38.41 Automatically generated by python-semantic-release * ci: reduce parallel runs for when checking if a dataset exists (#3035) The hope is that this will prevent many of the current [errors](https://github.com/embeddings-benchmark/mteb/actions/runs/17019125199/job/48245690831) * ci: Updating rerun delays to prevent false positives errors * ci: Updating rerun delays to prevent false positives errors * model: Add GreenNode Vietnamese Embedding models (#2994) * [ADD] 50 vietnamese dataset from vn-mteb * [UPDATE] task metadata * [UPDATE] import dependencies * [UPDATE] task metadata, bibtext citation * [UPDATE-TEST] test_model_meta * [UPDATE] sample_creation to machine-translated and LM verified * [ADD] sample creation machine-translated and LM verified * [ADD] Vietnamese Embedding models * [REMOVE] default fields metadata in Classfication tasks * [UPDATE] model to vi-vn language specific file * [FIX] lint * [FIX] model loader * model: add granite-embedding-english R2 models (#3050) * fix: Updated revision for jina-embeddings-v4 (#3046) * fix: jinav4 revision Signed-off-by: admin <bo.wang@jina.ai> * change revision instead of removing it Signed-off-by: admin <bo.wang@jina.ai> --------- Signed-off-by: admin <bo.wang@jina.ai> Co-authored-by: admin <bo.wang@jina.ai> * 1.38.42 Automatically generated by python-semantic-release * Fix 3 VN-MTEB Pair Classification tasks (#3053) * [ADD] 50 vietnamese dataset from vn-mteb * [UPDATE] task metadata * [UPDATE] import dependencies * [UPDATE] task metadata, bibtext citation * [UPDATE-TEST] test_model_meta * [UPDATE] sample_creation to machine-translated and LM verified * [ADD] sample creation machine-translated and LM verified * [ADD] Vietnamese Embedding models * [REMOVE] default fields metadata in Classfication tasks * [UPDATE] model to vi-vn language specific file * [FIX] lint * [FIX] model loader * [FIX] VN-MTEB 3 datasets PairClassification rename column * dataset: Add mbpp retrieval (#3037) * Add MBPP retrieval task - Code retrieval task based on 378 Python programming problems - Natural language queries matched to Python code implementations - Uses python-Code evaluation language for code-specific metrics - Includes proper citations and descriptive statistics * Add MBPPRetrieval to imports * Add descriptive statistics for MBPPRetrieval * Reformatting * Reformatting * Update tasks & benchmarks tables * dataset: Added wikisql retrieval (#3039) * Add WikiSQL retrieval task - Code retrieval task based on WikiSQL natural language to SQL dataset - Natural language questions matched to SQL query implementations - Uses sql-Code evaluation language for SQL-specific metrics - Includes proper citations and descriptive statistics * Add WikiSQLRetrieval to imports * Add descriptive statistics for WikiSQLRetrieval * Reformatting * Reformatting * Reformatting, correcting the revision * Update tasks & benchmarks tables * ci: Temporarily limit pytrec version to "pytrec-eval-terrier>=0.5.6, <0.5.8" to prevent errors try to fix CI * fix MBPPRetrieval revision (#3055) Update MBPPRetrieval.py Co-authored-by: Roman Solomatin <36135455+Samoed@users.noreply.github.com> * fix: Add VN-MTEB benchmark and Leaderboard (#2995) * [ADD] 50 vietnamese dataset from vn-mteb * [UPDATE] task metadata * [UPDATE] import dependencies * [UPDATE] task metadata, bibtext citation * [UPDATE-TEST] test_model_meta * [UPDATE] sample_creation to machine-translated and LM verified * [ADD] sample creation machine-translated and LM verified * [ADD] VN-MTEB benchmark and leaderboard * [FIX] wrong benchmark name * [REMOVE] default fields metadata in Classfication tasks * Update tasks & benchmarks tables * 1.38.43 Automatically generated by python-semantic-release * Add hc3finance retrieval (#3041) * Add HC3Finance retrieval task - Financial retrieval task based on HC3 Finance dataset - Financial questions matched to human and AI-generated content - Covers financial explanations, analysis, and educational content - Includes proper citations and descriptive statistics * Add HC3FinanceRetrieval to imports * Add descriptive statistics for HC3FinanceRetrieval * Reformatting * Reformatting, correcting the revision * Update mteb/tasks/Retrieval/eng/HC3FinanceRetrieval.py --------- Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> * Add finqa retrieval (#3042) * Add FinQA retrieval task - Financial numerical reasoning retrieval task based on FinQA dataset - Numerical financial questions matched to relevant document data - Covers earnings reports with tables and quantitative financial data - Includes proper citations and descriptive statistics * Add FinQARetrieval to imports * Add descriptive statistics for FinQARetrieval * Reformatting * Reformatting * Update mteb/tasks/Retrieval/eng/FinQARetrieval.py --------- Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> * Update tasks & benchmarks tables * Add FinanceBenchRetrieval task (#3044) * Add FinanceBenchRetrieval * Update mteb/tasks/Retrieval/eng/FinanceBenchRetrieval.py --------- Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> * Update tasks & benchmarks tables * Add FreshStackRetrieval task (#3043) * Add FreshStackRetrieval * Reformatting, correcting the revision * Dataset correction * Update tasks & benchmarks tables * dataset: Add ds1000 retrieval (#3038) * Add DS1000 retrieval task - Code retrieval task based on 1,000 data science programming problems - Natural language queries matched to Python data science code - Uses python-Code evaluation language for code-specific metrics - Covers pandas, numpy, matplotlib, scikit-learn, and scipy libraries * Add DS1000Retrieval to imports * Add descriptive statistics for DS1000Retrieval * Reformatting * Reformatting * Update tasks & benchmarks tables * Add ChatDoctorRetrieval (#3045) * Add ChatDoctorRetrieval * Reformatting, correcting the revision * Correct the dataset citation * Correcting due to comments * Update tasks & benchmarks tables * Correcting the (new) DS1000 dataset's revision (#3063) * Add DS1000 retrieval task - Code retrieval task based on 1,000 data science programming problems - Natural language queries matched to Python data science code - Uses python-Code evaluation language for code-specific metrics - Covers pandas, numpy, matplotlib, scikit-learn, and scipy libraries * Add DS1000Retrieval to imports * Add descriptive statistics for DS1000Retrieval * Reformatting * Reformatting * Add DS1000Retrieval task implementation * dataset: Add JinaVDR (#2942) * feat: added jinavdr benchmark * feat: added description for jinavdr * feat: fixed licenses and added bibtex * feat: made jinav4 compatible with vidore benchmark * feat: corrected query numbers * feat: removed print * feat: added max pixel argument for jina models * feat: score calculation on cpu * feat: adjust jina model for new mteb code * feat: code cleanup * feat: corrected bibtex * feat: make colpali run with jinavdr * feat: fixed comments * feat: better reference and fixed comments * feat: added date for tasks * feat: fixed missing metadata and bibtex * feat: added descriptions per dataset * Update tasks & benchmarks tables * model: Add CoDi-Embedding-V1 (#3054) * add codiemb-minicpm * replace codiemb_minicpm with codi_model * Update mteb/models/codi_model.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Update mteb/models/codi_model.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Update mteb/models/codi_model.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * update code * update code * reformat --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * fix: ensure that there are always relevant docs attached to query (#3058) * fix: ensure that there are always relevant docs attached to query Here is brief test that it doesn't influence scores: ```py t1 = mteb.get_task("TwitterHjerneRetrieval") meta = mteb.get_model_meta("minishlab/potion-base-2M") eval = mteb.MTEB(tasks=[t1]) res = eval.run(model=meta.load_model()) # before fix: res[0].get_score() # np.float64(0.02837) res[0].scores before_fix = { "train": [ { "ndcg_at_1": 0.02597, "ndcg_at_3": 0.02213, "ndcg_at_5": 0.0262, "ndcg_at_10": 0.02837, "ndcg_at_20": 0.04548, "ndcg_at_100": 0.13527, "ndcg_at_1000": 0.24507, "map_at_1": 0.00866, "map_at_3": 0.01317, "map_at_5": 0.0149, "map_at_10": 0.01562, "map_at_20": 0.01898, "map_at_100": 0.02968, "map_at_1000": 0.03841, "recall_at_1": 0.00866, "recall_at_3": 0.02056, "recall_at_5": 0.02922, "recall_at_10": 0.03355, "recall_at_20": 0.08268, "recall_at_100": 0.43766, "recall_at_1000": 1.0, "precision_at_1": 0.02597, "precision_at_3": 0.02165, "precision_at_5": 0.01818, "precision_at_10": 0.01039, "precision_at_20": 0.01234, "precision_at_100": 0.01481, "precision_at_1000": 0.0034, "mrr_at_1": 0.025974, "mrr_at_3": 0.041126, "mrr_at_5": 0.04632, "mrr_at_10": 0.048485, "mrr_at_20": 0.058356, "mrr_at_100": 0.070186, "mrr_at_1000": 0.071349, "nauc_ndcg_at_1_max": 0.33969, "nauc_ndcg_at_1_std": -0.202864, "nauc_ndcg_at_1_diff1": -0.127, "nauc_ndcg_at_3_max": 0.409376, "nauc_ndcg_at_3_std": -0.039352, "nauc_ndcg_at_3_diff1": -0.022816, "nauc_ndcg_at_5_max": 0.250499, "nauc_ndcg_at_5_std": -0.115263, "nauc_ndcg_at_5_diff1": -0.057017, "nauc_ndcg_at_10_max": 0.238696, "nauc_ndcg_at_10_std": -0.138396, "nauc_ndcg_at_10_diff1": -0.045287, "nauc_ndcg_at_20_max": 0.154456, "nauc_ndcg_at_20_std": -0.070635, "nauc_ndcg_at_20_diff1": 0.074499, "nauc_ndcg_at_100_max": -0.005753, "nauc_ndcg_at_100_std": -0.074738, "nauc_ndcg_at_100_diff1": -0.005851, "nauc_ndcg_at_1000_max": 0.109439, "nauc_ndcg_at_1000_std": -0.089797, "nauc_ndcg_at_1000_diff1": -0.021634, "nauc_map_at_1_max": 0.33969, "nauc_map_at_1_std": -0.202864, "nauc_map_at_1_diff1": -0.127, "nauc_map_at_3_max": 0.385244, "nauc_map_at_3_std": -0.080638, "nauc_map_at_3_diff1": -0.060991, "nauc_map_at_5_max": 0.294871, "nauc_map_at_5_std": -0.119069, "nauc_map_at_5_diff1": -0.06234, "nauc_map_at_10_max": 0.285698, "nauc_map_at_10_std": -0.132856, "nauc_map_at_10_diff1": -0.055015, "nauc_map_at_20_max": 0.236619, "nauc_map_at_20_std": -0.100673, "nauc_map_at_20_diff1": -0.002619, "nauc_map_at_100_max": 0.15345, "nauc_map_at_100_std": -0.138888, "nauc_map_at_100_diff1": -0.02257, "nauc_map_at_1000_max": 0.171402, "nauc_map_at_1000_std": -0.134644, "nauc_map_at_1000_diff1": -0.034477, "nauc_recall_at_1_max": 0.33969, "nauc_recall_at_1_std": -0.202864, "nauc_recall_at_1_diff1": -0.127, "nauc_recall_at_3_max": 0.375072, "nauc_recall_at_3_std": -0.009643, "nauc_recall_at_3_diff1": -0.089168, "nauc_recall_at_5_max": 0.147691, "nauc_recall_at_5_std": -0.128654, "nauc_recall_at_5_diff1": -0.084259, "nauc_recall_at_10_max": 0.141055, "nauc_recall_at_10_std": -0.165932, "nauc_recall_at_10_diff1": -0.060966, "nauc_recall_at_20_max": 0.043863, "nauc_recall_at_20_std": -0.028374, "nauc_recall_at_20_diff1": 0.157575, "nauc_recall_at_100_max": -0.157183, "nauc_recall_at_100_std": -0.019437, "nauc_recall_at_100_diff1": 0.013395, # "nauc_recall_at_1000_max": nan, # "nauc_recall_at_1000_std": nan, # "nauc_recall_at_1000_diff1": nan, "nauc_precision_at_1_max": 0.33969, "nauc_precision_at_1_std": -0.202864, "nauc_precision_at_1_diff1": -0.127, "nauc_precision_at_3_max": 0.406318, "nauc_precision_at_3_std": 0.007031, "nauc_precision_at_3_diff1": -0.034709, "nauc_precision_at_5_max": 0.178131, "nauc_precision_at_5_std": -0.112493, "nauc_precision_at_5_diff1": -0.045535, "nauc_precision_at_10_max": 0.167897, "nauc_precision_at_10_std": -0.150626, "nauc_precision_at_10_diff1": -0.027811, "nauc_precision_at_20_max": 0.081428, "nauc_precision_at_20_std": -0.042304, "nauc_precision_at_20_diff1": 0.17278, "nauc_precision_at_100_max": -0.150619, "nauc_precision_at_100_std": 0.016133, "nauc_precision_at_100_diff1": -0.065571, "nauc_precision_at_1000_max": -0.017244, "nauc_precision_at_1000_std": 0.046614, "nauc_precision_at_1000_diff1": -0.028258, "nauc_mrr_at_1_max": 0.33969, "nauc_mrr_at_1_std": -0.202864, "nauc_mrr_at_1_diff1": -0.127, "nauc_mrr_at_3_max": 0.409511, "nauc_mrr_at_3_std": -0.064671, "nauc_mrr_at_3_diff1": -0.01911, "nauc_mrr_at_5_max": 0.319584, "nauc_mrr_at_5_std": -0.103546, "nauc_mrr_at_5_diff1": -0.025109, "nauc_mrr_at_10_max": 0.309614, "nauc_mrr_at_10_std": -0.117564, "nauc_mrr_at_10_diff1": -0.019691, "nauc_mrr_at_20_max": 0.262976, "nauc_mrr_at_20_std": -0.092222, "nauc_mrr_at_20_diff1": 0.024507, "nauc_mrr_at_100_max": 0.256052, "nauc_mrr_at_100_std": -0.094249, "nauc_mrr_at_100_diff1": 0.012432, "nauc_mrr_at_1000_max": 0.260112, "nauc_mrr_at_1000_std": -0.098845, "nauc_mrr_at_1000_diff1": 0.009697, "main_score": 0.02837, "hf_subset": "default", "languages": ["dan-Latn"], } ] } # with update: res[0].get_score() # np.float64(0.02837) res[0].scores with_fix = { "train": [ { "ndcg_at_1": 0.02597, "ndcg_at_3": 0.02213, "ndcg_at_5": 0.0262, "ndcg_at_10": 0.02837, "ndcg_at_20": 0.04548, "ndcg_at_100": 0.13527, "ndcg_at_1000": 0.24507, "map_at_1": 0.00866, "map_at_3": 0.01317, "map_at_5": 0.0149, "map_at_10": 0.01562, "map_at_20": 0.01898, "map_at_100": 0.02968, "map_at_1000": 0.03841, "recall_at_1": 0.00866, "recall_at_3": 0.02056, "recall_at_5": 0.02922, "recall_at_10": 0.03355, "recall_at_20": 0.08268, "recall_at_100": 0.43766, "recall_at_1000": 1.0, "precision_at_1": 0.02597, "precision_at_3": 0.02165, "precision_at_5": 0.01818, "precision_at_10": 0.01039, "precision_at_20": 0.01234, "precision_at_100": 0.01481, "precision_at_1000": 0.0034, "mrr_at_1": 0.025974, "mrr_at_3": 0.041126, "mrr_at_5": 0.04632, "mrr_at_10": 0.048485, "mrr_at_20": 0.058356, "mrr_at_100": 0.070186, "mrr_at_1000": 0.071349, "nauc_ndcg_at_1_max": 0.33969, "nauc_ndcg_at_1_std": -0.202864, "nauc_ndcg_at_1_diff1": -0.127, "nauc_ndcg_at_3_max": 0.409376, "nauc_ndcg_at_3_std": -0.039352, "nauc_ndcg_at_3_diff1": -0.022816, "nauc_ndcg_at_5_max": 0.250499, "nauc_ndcg_at_5_std": -0.115263, "nauc_ndcg_at_5_diff1": -0.057017, "nauc_ndcg_at_10_max": 0.238696, "nauc_ndcg_at_10_std": -0.138396, "nauc_ndcg_at_10_diff1": -0.045287, "nauc_ndcg_at_20_max": 0.154456, "nauc_ndcg_at_20_std": -0.070635, "nauc_ndcg_at_20_diff1": 0.074499, "nauc_ndcg_at_100_max": -0.005753, "nauc_ndcg_at_100_std": -0.074738, "nauc_ndcg_at_100_diff1": -0.005851, "nauc_ndcg_at_1000_max": 0.109439, "nauc_ndcg_at_1000_std": -0.089797, "nauc_ndcg_at_1000_diff1": -0.021634, "nauc_map_at_1_max": 0.33969, "nauc_map_at_1_std": -0.202864, "nauc_map_at_1_diff1": -0.127, "nauc_map_at_3_max": 0.385244, "nauc_map_at_3_std": -0.080638, "nauc_map_at_3_diff1": -0.060991, "nauc_map_at_5_max": 0.294871, "nauc_map_at_5_std": -0.119069, "nauc_map_at_5_diff1": -0.06234, "nauc_map_at_10_max": 0.285698, "nauc_map_at_10_std": -0.132856, "nauc_map_at_10_diff1": -0.055015, "nauc_map_at_20_max": 0.236619, "nauc_map_at_20_std": -0.100673, "nauc_map_at_20_diff1": -0.002619, "nauc_map_at_100_max": 0.15345, "nauc_map_at_100_std": -0.138888, "nauc_map_at_100_diff1": -0.02257, "nauc_map_at_1000_max": 0.171402, "nauc_map_at_1000_std": -0.134644, "nauc_map_at_1000_diff1": -0.034477, "nauc_recall_at_1_max": 0.33969, "nauc_recall_at_1_std": -0.202864, "nauc_recall_at_1_diff1": -0.127, "nauc_recall_at_3_max": 0.375072, "nauc_recall_at_3_std": -0.009643, "nauc_recall_at_3_diff1": -0.089168, "nauc_recall_at_5_max": 0.147691, "nauc_recall_at_5_std": -0.128654, "nauc_recall_at_5_diff1": -0.084259, "nauc_recall_at_10_max": 0.141055, "nauc_recall_at_10_std": -0.165932, "nauc_recall_at_10_diff1": -0.060966, "nauc_recall_at_20_max": 0.043863, "nauc_recall_at_20_std": -0.028374, "nauc_recall_at_20_diff1": 0.157575, "nauc_recall_at_100_max": -0.157183, "nauc_recall_at_100_std": -0.019437, "nauc_recall_at_100_diff1": 0.013395, # "nauc_recall_at_1000_max": nan, # "nauc_recall_at_1000_std": nan, # "nauc_recall_at_1000_diff1": nan, "nauc_precision_at_1_max": 0.33969, "nauc_precision_at_1_std": -0.202864, "nauc_precision_at_1_diff1": -0.127, "nauc_precision_at_3_max": 0.406318, "nauc_precision_at_3_std": 0.007031, "nauc_precision_at_3_diff1": -0.034709, "nauc_precision_at_5_max": 0.178131, "nauc_precision_at_5_std": -0.112493, "nauc_precision_at_5_diff1": -0.045535, "nauc_precision_at_10_max": 0.167897, "nauc_precision_at_10_std": -0.150626, "nauc_precision_at_10_diff1": -0.027811, "nauc_precision_at_20_max": 0.081428, "nauc_precision_at_20_std": -0.042304, "nauc_precision_at_20_diff1": 0.17278, "nauc_precision_at_100_max": -0.150619, "nauc_precision_at_100_std": 0.016133, "nauc_precision_at_100_diff1": -0.065571, "nauc_precision_at_1000_max": -0.017244, "nauc_precision_at_1000_std": 0.046614, "nauc_precision_at_1000_diff1": -0.028258, "nauc_mrr_at_1_max": 0.33969, "nauc_mrr_at_1_std": -0.202864, "nauc_mrr_at_1_diff1": -0.127, "nauc_mrr_at_3_max": 0.409511, "nauc_mrr_at_3_std": -0.064671, "nauc_mrr_at_3_diff1": -0.01911, "nauc_mrr_at_5_max": 0.319584, "nauc_mrr_at_5_std": -0.103546, "nauc_mrr_at_5_diff1": -0.025109, "nauc_mrr_at_10_max": 0.309614, "nauc_mrr_at_10_std": -0.117564, "nauc_mrr_at_10_diff1": -0.019691, "nauc_mrr_at_20_max": 0.262976, "nauc_mrr_at_20_std": -0.092222, "nauc_mrr_at_20_diff1": 0.024507, "nauc_mrr_at_100_max": 0.256052, "nauc_mrr_at_100_std": -0.094249, "nauc_mrr_at_100_diff1": 0.012432, "nauc_mrr_at_1000_max": 0.260112, "nauc_mrr_at_1000_std": -0.098845, "nauc_mrr_at_1000_diff1": 0.009697, "main_score": 0.02837, "hf_subset": "default", "languages": ["dan-Latn"], } ] } # check with_fix == before_fix # True * restructure * format * relax pytrec versions * fix incorrect parsing * 1.38.44 Automatically generated by python-semantic-release * Correcting the JINA models with SentenceTransformerWrapper (#3071) * ci: Add stale workflow (#3066) * add stale workflow * add permissions * add bug label to bug issue template * revert bug issue and only look at more info needed issues * more accurate name * override default * fix: open_clip package validation (#3073) * 1.38.45 Automatically generated by python-semantic-release * fix: Update revision for qzhou models (#3069) * 1.38.46 Automatically generated by python-semantic-release * Fix the reference link for CoDi-Embedding-V1 (#3075) Fix reference link * fix: Add beta version of RTEB related benchmarks (#3048) * Add RTEB related benchmarks * Add RTEB related benchmarks * Correcting the task names in the RTEB benchmarks * Update mteb/leaderboard/benchmark_selector.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Adding the CURE dataset to RTEB benchmarks * Use the right language subset * Fix broken finance icon URL in RTEB benchmarks Replace broken libre-finance-dollar.svg with working libre-gui-price-tag.svg Validated all icon URLs and confirmed accessibility compliance * Add the rteb_benchmarks to the BENCHMARK_REGISTRY * Add the rteb_benchmarks to the BENCHMARK_REGISTRY * Add the rteb_benchmarks to the BENCHMARK_REGISTRY * Add the rteb_benchmarks to the BENCHMARK_REGISTRY * Add the rteb_benchmarks to the BENCHMARK_REGISTRY * Add the rteb_benchmarks to the BENCHMARK_REGISTRY * Add the rteb_benchmarks to the BENCHMARK_REGISTRY --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * 1.38.47 Automatically generated by python-semantic-release * fix: run `ruff check` on all files during ci (#3086) * fix: run `ruff check` on all files during ci * format * 1.38.48 Automatically generated by python-semantic-release * Move dev to dependency groups (#3088) add dependency groups * fix: Improving validate_task_to_prompt_name logs and error messages (#3079) * Improving validate_task_to_prompt_name logs and error messages * linter fixes * Adding None prompts tests * Update test_benchmark_sentence_transformer * Update mteb/leaderboard/benchmark_selector.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * fix: duplicate mteb multilingual variables (#3080) * fix benchmark naming * format * lint * Update tasks & benchmarks tables * model: mdbr-leaf models (#3081) * added MDBR leaf models * fixed revision for mdbr-leaf-ir * added model prompts * updated training datasets * fixed linting * lotte task reference --------- Co-authored-by: Robin Vujanic <robin.vujanic@mongodb.com> * 1.38.49 Automatically generated by python-semantic-release * CI: Set upper limit for xdist version (#3098) * Commentout bibtex formatting * Remove `-n auto` * get back bibtex * try limiting versions * revert coverage * revert coverage --------- Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> * Combine Plots and Tables into a Single (#3047) * feat - Combine Plots and Tables into a Single Tab #3009 * feat - Resize the plot to make it more readable * feat - Remove the (radar chart) * feat - Add a comment stating that it only shows the Top 5 models in the table. * feat - adjust layout * Update mteb/leaderboard/app.py * format --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> Co-authored-by: Kenneth Enevoldsen <kennethcenevoldsen@gmail.com> Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> * fix: Updating the default batch size calculation in the voyage models (#3091) * 1.38.50 Automatically generated by python-semantic-release * fix: Add @classmethod for @field_validators in TaskMetadata (#3100) * Align task prompt dict with `PromptType` (#3101) * align task prompt dict with `PromptType` * use value instead of enum * 1.38.51 Automatically generated by python-semantic-release * model: Add ModelMeta for OrdalieTech/Solon-embeddings-mini-beta-1.1 (#3090) * Add ModelMeta for OrdalieTech/Solon-embeddings-mini-beta-1.1 * Add training_datasets (common_corpus, fineweb, wiki_fr, private LLM-synth) * Format with ruff + add loader per review * Apply ruff format/fixes * Update mteb/models/ordalietech_solon_embeddings_mini_beta_1_1.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Update mteb/models/ordalietech_solon_embeddings_mini_beta_1_1.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Register OrdalieTech/Solon-embeddings-mini-beta-1.1 in overview (ModelMeta + loader) * Update mteb/models/ordalietech_solon_embeddings_mini_beta_1_1.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * fix import * Add memory_usage_mb=808.0 and required fields to ModelMeta * Fix 210 milions of parameters --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * fix: Allow closed datasets (#3059) * - Added an include_private parameter to the get_tasks() function that defaults to False - This ensures that by default, tests only run on public datasets - Tests can explicitly set include_private=True when needed to test private datasets - Added is_public: bool | None = None field to TaskMetadata - The field is optional and defaults to None (treated as public) - Updated the is_filled() method to exclude is_public from required fields - Added documentation * - Added an include_private parameter to the get_tasks() function that defaults to False - This ensures that by default, tests only run on public datasets - Tests can explicitly set include_private=True when needed to test private datasets - Added is_public: bool | None = None field to TaskMetadata - The field is optional and defaults to None (treated as public) - Updated the is_filled() method to exclude is_public from required fields - Added documentation * Correcting due to comments * Update mteb/abstasks/TaskMetadata.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/overview.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Removing the not used filter_tasks_by_privacy function * Correcting due to comments * Correcting due to comments * Correcting due to comments * Removing the test case * Rename the include_private parameter to exclude_private * Rename the include_private parameter to exclude_private * Add private tasks tests * Add private tasks tests * Update tests/test_tasks/test_private_tasks.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Add private tasks tests * Add private tasks tests * Add private tasks tests --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * 1.38.52 Automatically generated by python-semantic-release * Ci: test out GH models with welcoming new comers (#3112) test out GH models with welcoming new comers * ci: Dataset check on new PR (#3103) * add dataset check on new PR * add extract datasets * run as module * update startswith * update workflow name * add GitPython * export var * same shell session * address review comments * add to docs to say what this script does * add docs * model: add Youtu-Embedding-V1 (#3115) * add youtu models * add a blank line * fix the optional dependencies and lint the code * remove unused dependencies and reformat * revise prompt_type --------- Co-authored-by: springxchen <springxchen@tencent.com> * fix: add voyage quantization models (#3092) * Adding quantization support * Update mteb/models/voyage_models.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/model_meta.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Update mteb/model_meta.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Simplifying the quantization/output_dtype * Update mteb/model_meta.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * 1.38.53 Automatically generated by python-semantic-release * model: EmbeddingGemma 300M (#3129) * model: EmbeddingGemma 300M * Add license and revision * fix: Add dedicated display for RTEB benchmark results (#3089) * feat - remove special filtering, keep zero-shot, keep borda rank * feat - remove get_rteb_benchmark.py * feat - delete get_rteb_benchmark.py;RTEB_BENCHMARK_ENTRIES changes * feat -format * Update mteb/load_results/benchmark_results.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Update tasks & benchmarks tables * 1.38.54 Automatically generated by python-semantic-release * dataset: Add Dapfam patent retrieval tasks (#2946) * chore: add 'Patent retrieval' subtype to TaskMetadata * feat(retrieval): add DAPFAM patent retrieval tasks (+18 variants) * Dapfam patent retrieval PR #2946 : refactor DAPFAM tasks (explicit classes, license, metadata, custom definition explanation ...) * Dapfam patent retrieval PR #2946 : refactor DAPFAM tasks (explicit classes, license, metadata, custom definition explanation ...) * Update mteb/tasks/Retrieval/eng/DAPFAMPatentRetrieval.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/tasks/Retrieval/eng/DAPFAMPatentRetrieval.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/tasks/Retrieval/eng/DAPFAMPatentRetrieval.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/tasks/Retrieval/eng/DAPFAMPatentRetrieval.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/tasks/Retrieval/eng/DAPFAMPatentRetrieval.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/tasks/Retrieval/eng/DAPFAMPatentRetrieval.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Changes : - Added possibility to opt in or out of quantization through the "quantize" argument. - Added possibility to compute raw dot product without normalization. (to reproduce the paper method the "similarity" argument should be "cosine"). - Removed unecessary function and overhauled the tasks descriptions to be more clear. * Update mteb/tasks/Retrieval/eng/DAPFAMPatentRetrieval.py * Update mteb/tasks/Retrieval/eng/DAPFAMPatentRetrieval.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/tasks/Retrieval/eng/DAPFAMPatentRetrieval.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/tasks/Retrieval/eng/DAPFAMPatentRetrieval.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Changes made : - Overhauled task descriptions as well as naming to conform with the naming scheme of mteb retrieval tasks. - Similarity is now computed using the similarity function of the passed model. - Changed optional quantization method to conform with sentence transformers similarity function. to reproduce the paper metrics, one can use the following snippet : ```python from mteb import mteb from sentence_transformers import SentenceTransformer model_name = "Snowflake/snowflake-arctic-embed-m-v2.0" model = SentenceTransformer(model_name, model_kwargs={ "torch_dtype": "float16", }, trust_remote_code=True, ).cuda().eval() tasks = mteb.get_tasks(tasks=[ "DAPFAMInTitlAbsToTitlAbsClmRetrieval", "DAPFAMAllTitlAbsToTitlAbsClmRetrieval", "DAPFAMOutTitlAbsToTitlAbsClmRetrieval", add the other 3 remaining tasks ... ]) evaluation = mteb.MTEB(tasks=tasks) results = evaluation.run( model, output_folder=f"mteb_res/{model_name}", quantize=True, # if set to false or not set, the obtained ndcg@10 and map@10 will be ~0.001 higher encode_kwargs= {"batch_size" : 32} ) ``` * changed default value of quantization to false * added the import to all DAPFAM tasks; tested that the works; verified compliance with the checklist * Update mteb/tasks/Retrieval/eng/DAPFAMPatentRetrieval.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * added revision numbers to all dataset loading operations as well as the metadata itself * intermediate changes, refresh local branch * intermediate changes, refresh local branch again * scale back to standard evaluation with empty set exclusion, various cosmetic/formatting changes * minor cosmetic/formatting changes * fixed main metric to be ndcg_at_100 as in the paper * removed old code artifacts from previous versions * read appropriate loading arguments from task metadata, remove unecessary class attribute * reformat bibtex ( remark on the assertion since it tries to match literal string instead of bibtex formatting, format inconsistent with arXiv default), fixed metadata, parameters read from task metadata, all tests passed * refactor data loading to read from metadata class attributes --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Update tasks & benchmarks tables * Align max tokens (#3172) * Correct the VoyageAI model's batch creation/batch size calculation (#3185) Correct the batch creation * dataset: Adding JapaneseCode1Retrieval as the first non-public dataset (#3168) * Adding JapaneseCode1Retrieval as the first non-public dataset * Transformed dataset * Adding as private dataset to tests * Correct the private task test * Use the sample dataset as a reference * Use the sample dataset as a reference * fix ds loading * allow on forks * upd aciton * remove paths * try to trigger ci * add ref * add permissions * remove paths * add paths back * get back to pull request * rollback action * Trying to resolve the token/secret problem * Trying to resolve the token/secret problem * Update dataset_loading_pr.yml * Update dataset_loading_pr.yml * Try the latest datasets package (worked for me) * Try the latest datasets package (worked for me) * Try the latest datasets package (worked for me) * (last?) try * (last?) try * (last?) try * Reverting the changes * Exclude the private datasets from tests * Apply suggestions from code review --------- Co-authored-by: Roman Solomatin <36135455+Samoed@users.noreply.github.com> Co-authored-by: Solomatin Roman <samoed.roman@gmail.com> Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * fix: add version check for `embeddinggemma-300m` (#3189) add version check * dataset: Added a set of closed datasets (#3186) * Add 12 more closed datasets Extend the RTEB benchmarks * trust_remote_code * trust_remote_code * Enabling JapaneseCode1Retrieval in the RTEB benchmarks * Add closed datasets as private tasks * Correct due to the comment * Update tasks & benchmarks tables * fix: Edit ack & sponsors (#3187) * dataset: Update FaMTEB to Version 2 (#3157) * Update benchmark to version 2 * make others in benchmark selector one line code * small changes * update a few tasks metadata * update faintent license with correct form * remove redundant trust remote codes * fix hardnegatives revision * make lint * fix errors * apply suggestions * fix citation problem * add PR link to benchmark desc * remove duplicate dataset names in mcinext_models * update prompts --------- Co-authored-by: mehran <mehan.sarmadi16@gmail.com> * Update tasks & benchmarks tables * 1.38.55 Automatically generated by python-semantic-release * fix: Add conflicting dependencies to toml (#3191) fix conflict dependencies * 1.38.56 Automatically generated by python-semantic-release * fix: Correct metadata for ArguAna dataset (#3202) * Update tasks & benchmarks tables * 1.38.57 Automatically generated by python-semantic-release * model: Add BMRetriever (#3195) * model: Add BMRetriever * Update mteb/models/bmretriever_models.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Update mteb/models/bmretriever_models.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * fix: remove trust_remote_code option * feat: implement BMREtrieverWrapper based on InstructSentenceTransformerWrapper * refactor: update training datasets for bmretriever --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Revert "Ci: test out GH models with welcoming new comers" (#3206) Revert "Ci: test out GH models with welcoming new comers (#3112)" This reverts commit 73a35e0bb02e61108d50385f4c43fd7d1b16e984. * model: Add Codefuse models (#3205) * add codefuse models * add codefuse models * Update codefuse_models.py * lint codefuse.py * fix(models): ensure prompt_type is passed to format_instruction (#3216) * 1.38.58 Automatically generated by python-semantic-release * Adding Cohere's output_dimension and embedding_type parameter (#3204) * Adding Cohere's output_dimension and embedding_type parameter Cohere's embed-v4 binary and int8 * Correcting due to comments * dataset: add swedish cpc patent classifications to mteb (#3072) * feat: add swedish cpc patent classifications to mteb * fix: formatting and init imports * fix: update mteb task according to feedback * fix: perform citation and code formatting * fix: add train and test split for both datasets * fix: AttributeError in ColPaliEngineWrapper similarity method (#3177) * fix: delete kwargs for similarity score in ColPaliEngineWrapper for method behavior * chore: fix colpali_models similarity handle device * Update tasks & benchmarks tables * 1.38.59 Automatically generated by python-semantic-release * fix: prevent EOS token truncation (#3218) * fix(models): prevent EOS token truncation for BMRetriever * refactor(models): refactor tokenizer setup in `InstructSentenceTransformerWrapper` * fix(models): correct eos token handling in `BMRetrieverWrapper` * 1.38.60 Automatically generated by python-semantic-release * Update giga embeddings (#3210) * update giga embeddings * update giga embeddings * 3b-september-2025 * fixed * lint * Update mteb/models/ru_sentence_models.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * change revision due to flash-attn dependency * change apply_instruction_to_passages --------- Co-authored-by: Kolodin Egor <eikolodin@sberbank.ru> Co-authored-by: Roman Solomatin <36135455+Samoed@users.noreply.github.com> Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> Co-authored-by: Неизвестный Пользователь722497 <dolegosmirnov@sberbank.ru> * fix: Refactor split create_tables into static Benchmark methods (#3126) * feat - Split create_tables into static Benchmark methods * feat - format * Update mteb/leaderboard/table.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * feat - remove search query;take benchmark result as input;addressing the circular import, * feat - format * Update mteb/benchmarks/benchmark.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/benchmarks/benchmark.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * feat - use to_dataframe;clean table.py;move creat_table * feat - fix circular import * feat - clean-up * feat - format --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * 1.38.61 Automatically generated by python-semantic-release * Extending the RTEB benchmark (#3223) Adding another voyageai model * Update tasks & benchmarks tables * model: New qzmodel (#3211) * Update qzhou_models.py * Update qzhou_models.py * reformat script code * Update configuration * According to our new decision, the model name has been changed to "QZhou-Embedding-Zh". * Fix variable naming issues. * model: Update Youtu embedding model (#3227) * add youtu models * add a blank line * fix the optional dependencies and lint the code * remove unused dependencies and reformat * revise prompt_type * update youtu_models --------- Co-authored-by: springxchen <springxchen@tencent.com> * dataset: Add Software Issue Localization Datasets (#3178) * add software issue localization datasets * add software issue localization datasets * update and add multilingual datasets * fix citation format issues * Update mteb/tasks/Reranking/eng/SWEbenchVerifiedReranking.py * fix linting issues --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Update tasks & benchmarks tables * feat: Officially include RTEB in the leaderboard (#3222) * feat - adjust Rteb's Benchmark * feat - add blank * fix menu names * Update mteb/leaderboard/benchmark_selector.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * moving around tasks * fix: Update RTEB summary columns (#3226) * fix(models): ensure prompt_type is passed to format_instruction (#3216) * 1.38.58 Automatically generated by python-semantic-release * Adding Cohere's output_dimension and embedding_type parameter (#3204) * Adding Cohere's output_dimension and embedding_type parameter Cohere's embed-v4 binary and int8 * Correcting due to comments * dataset: add swedish cpc patent classifications to mteb (#3072) * feat: add swedish cpc patent classifications to mteb * fix: formatting and init imports * fix: update mteb task according to feedback * fix: perform citation and code formatting * fix: add train and test split for both datasets * fix: AttributeError in ColPaliEngineWrapper similarity method (#3177) * fix: delete kwargs for similarity score in ColPaliEngineWrapper for method behavior * chore: fix colpali_models similarity handle device * Update tasks & benchmarks tables * 1.38.59 Automatically generated by python-semantic-release * fix: prevent EOS token truncation (#3218) * fix(models): prevent EOS token truncation for BMRetriever * refactor(models): refactor tokenizer setup in `InstructSentenceTransformerWrapper` * fix(models): correct eos token handling in `BMRetrieverWrapper` * 1.38.60 Automatically generated by python-semantic-release * Update giga embeddings (#3210) * update giga embeddings * update giga embeddings * 3b-september-2025 * fixed * lint * Update mteb/models/ru_sentence_models.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * change revision due to flash-attn dependency * change apply_instruction_to_passages --------- Co-authored-by: Kolodin Egor <eikolodin@sberbank.ru> Co-authored-by: Roman Solomatin <36135455+Samoed@users.noreply.github.com> Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> Co-authored-by: Неизвестный Пользователь722497 <dolegosmirnov@sberbank.ru> * fix: Refactor split create_tables into static Benchmark methods (#3126) * feat - Split create_tables into static Benchmark methods * feat - format * Update mteb/leaderboard/table.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * feat - remove search query;take benchmark result as input;addressing the circular import, * feat - format * Update mteb/benchmarks/benchmark.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update mteb/benchmarks/benchmark.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * feat - use to_dataframe;clean table.py;move creat_table * feat - fix circular import * feat - clean-up * feat - format --------- Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * 1.38.61 Automatically generated by python-semantic-release * Extending the RTEB benchmark (#3223) Adding another voyageai model * Update tasks & benchmarks tables * feat - filter_by_privacy * feat - add new fields for rteb part * feat - getattr * feat - adjust privacy filter logic * feat - enhance summary table column renaming and add 'is_public' field mapping * fix: remove unused 'is_public' attribute from TaskResult --------- Co-authored-by: Yongbin Choi <whybe.choi@gmail.com> Co-authored-by: semantic-release <semantic-release> Co-authored-by: fzoll <5575946+fzoll@users.noreply.github.com> Co-authored-by: Atheer <atheer2104@protonmail.com> Co-authored-by: Yong woo Song <ywsong.dev@kakao.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Egor <31567312+ekolodin@users.noreply.github.com> Co-authored-by: Kolodin Egor <eikolodin@sberbank.ru> Co-authored-by: Roman Solomatin <36135455+Samoed@users.noreply.github.com> Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> Co-authored-by: Неизвестный Пользователь722497 <dolegosmirnov@sberbank.ru> Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> Co-authored-by: smile <smile@pinai.io> Co-authored-by: ethan <smiletoye@gmail.com> * removed show_rteb args * avoid defining function where we can just use the metadata * minor fixes * minor fixes * fix: Correct logic for filtering public tasks in ModelResult class (#3230) Co-authored-by: ethan <smiletoye@gmail.com> --------- Co-authored-by: q275343119 <275343119@qq.com> Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> Co-authored-by: 笑尿伊人 <44760272+q275343119@users.noreply.github.com> Co-authored-by: Yongbin Choi <whybe.choi@gmail.com> Co-authored-by: fzoll <5575946+fzoll@users.noreply.github.com> Co-authored-by: Atheer <atheer2104@protonmail.com> Co-authored-by: Yong woo Song <ywsong.dev@kakao.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Egor <31567312+ekolodin@users.noreply.github.com> Co-authored-by: Kolodin Egor <eikolodin@sberbank.ru> Co-authored-by: Roman Solomatin <36135455+Samoed@users.noreply.github.com> Co-authored-by: Неизвестный Пользователь722497 <dolegosmirnov@sberbank.ru> Co-authored-by: smile <smile@pinai.io> Co-authored-by: ethan <smiletoye@gmail.com> * Update tasks & benchmarks tables * 1.39.0 Automatically generated by python-semantic-release * fix: Add submission references for RTEB (#3233) * fix: Add rteb submission references and improve descriptions. * Added evaluation request * added field for tasks * 1.39.1 Automatically generated by python-semantic-release * dataset: add human tasks and benchmark (#3214) * Human Subsets Tasks * Fixed Multilingual Classification Subset * linting * fix citations format * make lint * fix tests * remove human folder * fix relative imports * add adapted_from for all human subsets * fix pydantic errors * add benchmark object * make benchmark discoverable * bibtex test * Apply suggestion Co-authored-by: Kenneth Enevoldsen <kennethcenevoldsen@gmail.com> * Apply suggestions from code review Co-authored-by: Kenneth Enevoldsen <kennethcenevoldsen@gmail.com> * rename & reupload * upd tests * upd tests again * add model * add benchmark to leaderboard * change branch of leaderboard * remove branch of load data * fix model meta path * make mteb importable * update repo * Update mteb/benchmarks/benchmarks/benchmarks.py * Update mteb/leaderboard/benchmark_selector.py * Update mteb/load_results/load_results.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> --------- Co-authored-by: Adnan El Assadi <aassadi22@ku.edu.tr> Co-authored-by: Isaac Chung <chungisaac1217@gmail.com> Co-authored-by: Kenneth Enevoldsen <kennethcenevoldsen@gmail.com> Co-authored-by: AdnanElAssadi56 <115242814+AdnanElAssadi56@users.noreply.github.com> * Update tasks & benchmarks tables * Remove 'HUME(v1)' from leaderboard benchmark (#3236) * Remove 'HUME(v1)' from leaderboard benchmark * lint * docs: Update adding benchmark documentation (#3229) * update adding_a_benchmark.md documentation * fix numbers * fix: Further specified macro-language code for Norwegian (#3228) * fix: Further specified macro-language code for Norwegian "nor" is a macro-language code that covers bokmål and nynorsk (both norwegian), but this means that these datasets will be missed if using "nob" or "nno". Specifying it like this should allow this. * furhter specified macro language "nor" * Update tasks & benchmarks tables * 1.39.2 Automatically generated by python-semantic-release * fix max tokens (#3243) * fix python39 transformers compatibility (#3254) * fix python39 transformers * fix * Aggregate by subset for HUMEv1 (#3255) aggregate by subset for HUMEv1 * Update tasks & benchmarks tables * Fix AbsTaskTextRegression task (#3257) Fix AbsTaskTextRegression * Added Japanese to Retrieval (#3252) * feat - add Japanese * feat - use mteb.get_benchmark * fix - 3.9 test error * Revert "fix - 3.9 test error" This reverts commit 6bfee53cff48304cc22d8248aa275dcc9e385475. * fix - 3.9 test error * Update tasks & benchmarks tables * fix bm25 on small datasets (#3261) * fix: Move zero-shot percentage calculation to the end of summary (#3231) * Refactor: Move zero-shot percentage calculation to the end of summary table creation which only apply to RTEB table. * Update RTEB benchmark name from "RTEB(beta)" to "RTEB" for consistency in display. * feat - RTEB(beta) * feat - remove Zero-shot --------- Co-authored-by: ethan <smiletoye@gmail.com> * model: Add ReasonIR (#3221) * model: Add ReasonIR * Update mteb/models/reasonir_model.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * Update mteb/models/reasonir_model.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * update n_parameters of ReasonIR Co-authored-by: Niklas <n.muennighoff@gmail.com> --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> Co-authored-by: Niklas <n.muennighoff@gmail.com> * fix: Only pin model name and rank (#3263) Currently we pin 3 columns, this makes it hard or impossible to view on phones. The 3rd column is also no longer garuanteed as RTEB leaderboard does not use the zero-shot column * 1.39.3 Automatically generated by python-semantic-release * fix: resolve flash-attention dependency issue (#3265) * fix: Only pin model name and rank Currently we pin 3 columns, this makes it hard or impossible to view on phones. The 3rd column is also no longer garuanteed as RTEB leaderboard does not use the zero-shot column * fix: resolve flash-attention dependency issue This has been tested and works. fixed Resolve flash-attention dependency issues Fixes #3240 * 1.39.4 Automatically generated by python-semantic-release * fix: Add retry and token counting in Cohere models (#3253) * Retry and token counting in Cohere models * Retry and token counting in Cohere models * Retry and token counting in Cohere models --------- Co-authored-by: Roman Solomatin <36135455+Samoed@users.noreply.github.com> * 1.39.5 Automatically generated by python-semantic-release * Align MIEB leaderboards with paper (#3272) * sort by mean task type and use pure rank for MIEB LBs * lint * rename task type column for readability * fix: add prompt for MIRACLRetrievalHardNegatives (#3266) * add prompt for MIRACLRetrievalHardNegatives * add `MIRACLRetrievalHardNegatives.v2` * Update mteb/tasks/Retrieval/multilingual/MIRACLRetrieval.py Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * move common metadata to dict --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> Co-authored-by: Kenneth Enevoldsen <kenevoldsen@pm.me> * Update tasks & benchmarks tables * Add Regression task mock (#3271) * 1.39.6 Automatically generated by python-semantic-release * fix: Change language for task SlovakMovieReviewSentimentClassification (#3296) * Update tasks & benchmarks tables * 1.39.7 Automatically generated by python-semantic-release * Add english code retriever model (#3302) * Add en code retriever model * fix model_name * Update mteb/models/en_code_retriever.py Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * correct lint --------- Co-authored-by: Roman Solomatin <samoed.roman@gmail.com> * docs: fix typos in `docs/adding_a_benchmark.md` (#3344) * BREAKING: v2.0.0 (#1433) * [v2] Merge…

AdnanElAssadi56 added 2 commits September 25, 2025 19:05

Human Subsets Tasks

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Samoed commented Sep 25, 2025

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MTEB Human Tasks #3213

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AdnanElAssadi56 and others added 8 commits September 25, 2025 15:26

linting

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fix citations format

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make lint

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fix tests

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remove human folder

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fix relative imports

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add adapted_from for all human subsets

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isaac-chung changed the title ~~Add human tasks~~ Add human tasks and benchmark Sep 27, 2025

isaac-chung added 3 commits September 27, 2025 20:24

add benchmark object

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Samoed changed the title ~~Add human tasks and benchmark~~ dataset: add human tasks and benchmark Sep 29, 2025

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upd tests

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Samoed added the new benchmark Issues related to adding a new benchmark label Sep 29, 2025

AdnanElAssadi56 and others added 2 commits October 1, 2025 00:49

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isaac-chung enabled auto-merge (squash) October 2, 2025 05:40

isaac-chung merged commit 48a01fc into main Oct 2, 2025
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isaac-chung deleted the human_tasks branch October 2, 2025 06:15

Samoed mentioned this pull request Oct 5, 2025

Measure human performance on mteb #2272

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