Add results (#40)

* Add

* Add res

* fix: reduce sizes of files and added makefile command

* Add

* Add res

* formatted flores files

* Add

* Add res

* make preprush

* Add OAI T3Small MMTEB

* update ci dependencies to >3.9

* tmp

* reduce large file sizes

* Add overview table to readme

* Add missing TE3L results

* Make prepush

* Add res

* reduce size

* AddRes

* Add

* fix: run make pre-push

* add revision to openai text-embedding-large, add "openai/" to model name

* minor fix to model meta

* make sure pip is upgraded installing packages

---------

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

.github/workflows/test.yml

@@ -17,7 +17,6 @@ jobs:
       matrix:
         os: [ubuntu-latest] #, macos-latest, windows-latest]
         python-version: ["3.9"]
-
     steps:
       - uses: actions/checkout@v3
 

.gitignore

@@ -10,3 +10,6 @@ tmp.py
 
 # MacOS
 .DS_Store
+
+# UV
+uv.lock

README.md

@@ -2,4 +2,20 @@
 benchmark: mteb
 type: evaluation
 submission_name: MTEB
----
+---
+
+This repository contain the results of the embedding benchmark evaluated using the package `mteb`.
+
+
+| Reference           |                                                                                          |
+| ------------------- | ---------------------------------------------------------------------------------------- |
+| 🦾 **[Leaderboard]** | An up to date leaderboard of embedding models                                            |
+| 📚 **[mteb]**        | Guides and instructions on how to use `mteb`, including running, submitting scores, etc. |
+| 🙋 **[Questions]**   | Questions about the results                                                              |
+| 🙋 **[Issues]**      | Issues or bugs you have found                                                            |
+
+
+[Leaderboard]: https://huggingface.co/spaces/mteb/leaderboard
+[mteb]: https://github.com/embeddings-benchmark/mteb
+[Questions]: https://github.com/embeddings-benchmark/mteb/discussions
+[Issues]: https://github.com/embeddings-benchmark/mteb/issues

makefile

@@ -1,7 +1,7 @@
 install-for-tests:
 	@echo "--- Installing dependencies for tests ---"
-	# just use the dev dependencies from mteb to keep everything compatible
-	pip install "mteb[dev]>=1.13.0"
+	pip install pip --upgrade
+	pip install .
 
 test:
 	@echo "--- Running tests ---"

pyproject.toml

@@ -0,0 +1,7 @@
+[project]
+name = "results"
+version = "0.1.0"
+description = "The result repository for mteb"
+readme = "README.md"
+requires-python = ">=3.9"
+dependencies = ["mteb[dev]>=1.13.0"]

results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/AILAStatutes.json

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+}

results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/AfriSentiClassification.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/AlloProfClusteringS2S.v2.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/AlloprofReranking.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/AmazonCounterfactualClassification.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/ArXivHierarchicalClusteringP2P.json

@@ -0,0 +1,46 @@
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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/ArXivHierarchicalClusteringS2S.json

@@ -0,0 +1,46 @@
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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/ArguAna.json

@@ -0,0 +1,158 @@
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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/ArmenianParaphrasePC.json

@@ -0,0 +1,58 @@
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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/BUCC.v2.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/BigPatentClustering.v2.json

@@ -0,0 +1,34 @@
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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/BiorxivClusteringP2P.v2.json

@@ -0,0 +1,34 @@
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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/BornholmBitextMining.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/BrazilianToxicTweetsClassification.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/BulgarianStoreReviewSentimentClassfication.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/CEDRClassification.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/CLSClusteringP2P.v2.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/CSFDSKMovieReviewSentimentClassification.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/CTKFactsNLI.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/CataloniaTweetClassification.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/CovidRetrieval.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/CyrillicTurkicLangClassification.json

@@ -0,0 +1,81 @@
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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/CzechProductReviewSentimentClassification.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/DBpediaClassification.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/DalajClassification.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/DiaBlaBitextMining.json

@@ -0,0 +1,35 @@
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+}

results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/EstonianValenceClassification.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/FaroeseSTS.json

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+}

results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/FilipinoShopeeReviewsClassification.json

@@ -0,0 +1,137 @@
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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/FinParaSTS.json

@@ -0,0 +1,43 @@
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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/FinancialPhrasebankClassification.json

@@ -0,0 +1,73 @@
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+}

results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/GermanSTSBenchmark.json

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+  "task_name": "GermanSTSBenchmark"
+}

results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/GreekLegalCodeClassification.json

@@ -0,0 +1,137 @@
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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/GujaratiNewsClassification.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/HALClusteringS2S.v2.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/IndicCrosslingualSTS.json

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results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/IndicGenBenchFloresBitextMining.json

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+}

results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/IndicLangClassification.json

@@ -0,0 +1,96 @@
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+}

results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/IndonesianIdClickbaitClassification.json

@@ -0,0 +1,95 @@
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+}

results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/IsiZuluNewsClassification.json

@@ -0,0 +1,73 @@
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+}

results/Alibaba-NLP__gte-Qwen2-7B-instruct/e26182b2122f4435e8b3ebecbf363990f409b45b/ItaCaseholdClassification.json

@@ -0,0 +1,73 @@
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+}