Add results for baseline models for all benchmarks (#153)

* Add base results for a bunch of models

* Added more results

* add

* add more

* added more data - need an update to mteb

* more model results

* adding runs

* more hot models

* Add more model run

* Added more model runs

* Added more runs

* more runs

* add

* remove running

.gitignore

@@ -22,4 +22,7 @@ tmp.py
 uv.lock
 
 build/
-results.egg-info/
+results.egg-info/
+
+# codecarbon
+.codecarbon.lock

results/intfloat__multilingual-e5-base/d13f1b27baf31030b7fd040960d60d909913633f/model_meta.json

@@ -1 +1 @@
-{"name": "intfloat/multilingual-e5-base", "revision": "d13f1b27baf31030b7fd040960d60d909913633f", "release_date": "2024-02-08", "languages": ["afr_Latn", "amh_Latn", "ara_Latn", "asm_Latn", "aze_Latn", "bel_Latn", "bul_Latn", "ben_Latn", "ben_Beng", "bre_Latn", "bos_Latn", "cat_Latn", "ces_Latn", "cym_Latn", "dan_Latn", "deu_Latn", "ell_Latn", "eng_Latn", "epo_Latn", "spa_Latn", "est_Latn", "eus_Latn", "fas_Latn", "fin_Latn", "fra_Latn", "fry_Latn", "gle_Latn", "gla_Latn", "glg_Latn", "guj_Latn", "hau_Latn", "heb_Latn", "hin_Latn", "hin_Deva", "hrv_Latn", "hun_Latn", "hye_Latn", "ind_Latn", "isl_Latn", "ita_Latn", "jpn_Latn", "jav_Latn", "kat_Latn", "kaz_Latn", "khm_Latn", "kan_Latn", "kor_Latn", "kur_Latn", "kir_Latn", "lat_Latn", "lao_Latn", "lit_Latn", "lav_Latn", "mlg_Latn", "mkd_Latn", "mal_Latn", "mon_Latn", "mar_Latn", "msa_Latn", "mya_Latn", "nep_Latn", "nld_Latn", "nob_Latn", "orm_Latn", "ori_Latn", "pan_Latn", "pol_Latn", "pus_Latn", "por_Latn", "ron_Latn", "rus_Latn", "san_Latn", "snd_Latn", "sin_Latn", "slk_Latn", "slv_Latn", "som_Latn", "sqi_Latn", "srp_Latn", "sun_Latn", "swe_Latn", "swa_Latn", "tam_Latn", "tam_Taml", "tel_Latn", "tel_Telu", "tha_Latn", "tgl_Latn", "tur_Latn", "uig_Latn", "ukr_Latn", "urd_Latn", "urd_Arab", "uzb_Latn", "vie_Latn", "xho_Latn", "yid_Latn", "zho_Hant", "zho_Hans"], "n_parameters": 278000000, "max_tokens": 514.0, "embed_dim": 768, "license": "mit", "open_weights": true, "public_training_code": null, "framework": ["Sentence Transformers", "PyTorch"], "reference": "https://huggingface.co/intfloat/multilingual-e5-base", "similarity_fn_name": "cosine", "use_instructions": true, "training_datasets": {"MSMARCO": ["train"], "MSMARCOHardNegatives": ["train"], "NanoMSMARCORetrieval": ["train"], "MSMARCO-PL": ["train"], "NQ": ["train"], "NQHardNegatives": ["train"], "NanoNQRetrieval": ["train"], "NQ-PL": ["train"]}, "adapted_from": null, "superseded_by": null, "loader": "sentence_transformers_loader"}
+{"name": "intfloat/multilingual-e5-base", "revision": "d13f1b27baf31030b7fd040960d60d909913633f", "release_date": "2024-02-08", "languages": ["afr_Latn", "amh_Latn", "ara_Latn", "asm_Latn", "aze_Latn", "bel_Latn", "bul_Latn", "ben_Latn", "ben_Beng", "bre_Latn", "bos_Latn", "cat_Latn", "ces_Latn", "cym_Latn", "dan_Latn", "deu_Latn", "ell_Latn", "eng_Latn", "epo_Latn", "spa_Latn", "est_Latn", "eus_Latn", "fas_Latn", "fin_Latn", "fra_Latn", "fry_Latn", "gle_Latn", "gla_Latn", "glg_Latn", "guj_Latn", "hau_Latn", "heb_Latn", "hin_Latn", "hin_Deva", "hrv_Latn", "hun_Latn", "hye_Latn", "ind_Latn", "isl_Latn", "ita_Latn", "jpn_Latn", "jav_Latn", "kat_Latn", "kaz_Latn", "khm_Latn", "kan_Latn", "kor_Latn", "kur_Latn", "kir_Latn", "lat_Latn", "lao_Latn", "lit_Latn", "lav_Latn", "mlg_Latn", "mkd_Latn", "mal_Latn", "mon_Latn", "mar_Latn", "msa_Latn", "mya_Latn", "nep_Latn", "nld_Latn", "nob_Latn", "orm_Latn", "ori_Latn", "pan_Latn", "pol_Latn", "pus_Latn", "por_Latn", "ron_Latn", "rus_Latn", "san_Latn", "snd_Latn", "sin_Latn", "slk_Latn", "slv_Latn", "som_Latn", "sqi_Latn", "srp_Latn", "sun_Latn", "swe_Latn", "swa_Latn", "tam_Latn", "tam_Taml", "tel_Latn", "tel_Telu", "tha_Latn", "tgl_Latn", "tur_Latn", "uig_Latn", "ukr_Latn", "urd_Latn", "urd_Arab", "uzb_Latn", "vie_Latn", "xho_Latn", "yid_Latn", "zho_Hant", "zho_Hans"], "n_parameters": 278000000, "memory_usage_mb": 1061.0, "max_tokens": 514.0, "embed_dim": 768, "license": "mit", "open_weights": true, "public_training_code": null, "public_training_data": null, "framework": ["Sentence Transformers", "PyTorch"], "reference": "https://huggingface.co/intfloat/multilingual-e5-base", "similarity_fn_name": "cosine", "use_instructions": true, "training_datasets": {"MSMARCO": ["train"], "MSMARCOHardNegatives": ["train"], "NanoMSMARCORetrieval": ["train"], "MSMARCO-PL": ["train"], "mMARCO-NL": ["train"], "NQ": ["train"], "NQHardNegatives": ["train"], "NanoNQRetrieval": ["train"], "NQ-PL": ["train"], "NQ-NL": ["train"], "FEVER": ["train"], "FEVERHardNegatives": ["train"], "FEVER-NL": ["train"], "HotpotQA": ["train"], "HotpotQAHardNegatives": ["train"], "HotpotQA-PL": ["train"], "HotpotQA-NL": ["train"], "MIRACLRetrieval": ["train"], "MIRACLRetrievalHardNegatives": ["train"], "MIRACLReranking": ["train"], "MrTidyRetrieval": ["train"]}, "adapted_from": "FacebookAI/xlm-roberta-base", "superseded_by": null, "is_cross_encoder": null, "modalities": ["text"], "loader": "sentence_transformers_loader"}

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/ArXivHierarchicalClusteringP2P.json

@@ -0,0 +1,46 @@
+{
+  "dataset_revision": "0bbdb47bcbe3a90093699aefeed338a0f28a7ee8",
+  "task_name": "ArXivHierarchicalClusteringP2P",
+  "mteb_version": "1.36.26",
+  "scores": {
+    "test": [
+      {
+        "v_measures": {
+          "Level 0": [
+            0.580181,
+            0.539993,
+            0.503537,
+            0.510407,
+            0.527832,
+            0.546085,
+            0.526767,
+            0.542954,
+            0.492944,
+            0.509889
+          ],
+          "Level 1": [
+            0.596262,
+            0.591529,
+            0.559427,
+            0.572937,
+            0.603085,
+            0.559872,
+            0.599761,
+            0.590964,
+            0.579028,
+            0.603659
+          ]
+        },
+        "v_measure": 0.556856,
+        "v_measure_std": 0.035376,
+        "main_score": 0.556856,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ]
+      }
+    ]
+  },
+  "evaluation_time": 6.958680629730225,
+  "kg_co2_emissions": 0.00013216813014394022
+}

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/ArXivHierarchicalClusteringS2S.json

@@ -0,0 +1,46 @@
+{
+  "dataset_revision": "b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3",
+  "task_name": "ArXivHierarchicalClusteringS2S",
+  "mteb_version": "1.36.26",
+  "scores": {
+    "test": [
+      {
+        "v_measures": {
+          "Level 0": [
+            0.533462,
+            0.465792,
+            0.55323,
+            0.517584,
+            0.529703,
+            0.543309,
+            0.488845,
+            0.520965,
+            0.527078,
+            0.506556
+          ],
+          "Level 1": [
+            0.548532,
+            0.525384,
+            0.57581,
+            0.554894,
+            0.559749,
+            0.572276,
+            0.573463,
+            0.572442,
+            0.522958,
+            0.541122
+          ]
+        },
+        "v_measure": 0.536658,
+        "v_measure_std": 0.028347,
+        "main_score": 0.536658,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ]
+      }
+    ]
+  },
+  "evaluation_time": 5.876571416854858,
+  "kg_co2_emissions": 0.00010187011710630339
+}

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/ArguAna.json

@@ -0,0 +1,158 @@
+{
+  "dataset_revision": "c22ab2a51041ffd869aaddef7af8d8215647e41a",
+  "task_name": "ArguAna",
+  "mteb_version": "1.36.26",
+  "scores": {
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+        "map_at_20": 0.4663,
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+        "map_at_1000": 0.46882,
+        "recall_at_1": 0.30654,
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+        "recall_at_100": 0.97653,
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+        "precision_at_10": 0.08087,
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+        "nauc_mrr_at_1000_diff1": 0.095823,
+        "main_score": 0.54357,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ]
+      }
+    ]
+  },
+  "evaluation_time": 89.08000540733337,
+  "kg_co2_emissions": 0.002318251662421719
+}

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/AskUbuntuDupQuestions.json

@@ -0,0 +1,26 @@
+{
+  "dataset_revision": "2000358ca161889fa9c082cb41daa8dcfb161a54",
+  "task_name": "AskUbuntuDupQuestions",
+  "mteb_version": "1.36.26",
+  "scores": {
+    "test": [
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+        "mrr": 0.720784,
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+        "nAUC_map_diff1": 0.143458,
+        "nAUC_mrr_max": 0.357551,
+        "nAUC_mrr_std": 0.224028,
+        "nAUC_mrr_diff1": 0.268828,
+        "main_score": 0.592387,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ]
+      }
+    ]
+  },
+  "evaluation_time": 5.478834867477417,
+  "kg_co2_emissions": 0.00014206468097306338
+}

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/BIOSSES.json

@@ -0,0 +1,26 @@
+{
+  "dataset_revision": "d3fb88f8f02e40887cd149695127462bbcf29b4a",
+  "task_name": "BIOSSES",
+  "mteb_version": "1.36.26",
+  "scores": {
+    "test": [
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+        "pearson": 0.863404,
+        "spearman": 0.845736,
+        "cosine_pearson": 0.863404,
+        "cosine_spearman": 0.845736,
+        "manhattan_pearson": 0.841476,
+        "manhattan_spearman": 0.842116,
+        "euclidean_pearson": 0.842946,
+        "euclidean_spearman": 0.845736,
+        "main_score": 0.845736,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ]
+      }
+    ]
+  },
+  "evaluation_time": 0.5543363094329834,
+  "kg_co2_emissions": 1.3465482019777075e-05
+}

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/Banking77Classification.json

@@ -0,0 +1,73 @@
+{
+  "dataset_revision": "0fd18e25b25c072e09e0d92ab615fda904d66300",
+  "task_name": "Banking77Classification",
+  "mteb_version": "1.36.26",
+  "scores": {
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+        "scores_per_experiment": [
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+          {
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+          {
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+          {
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+          {
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+          {
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+          }
+        ],
+        "main_score": 0.749188,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ]
+      }
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results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/BiorxivClusteringP2P.v2.json

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results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/CQADupstackGamingRetrieval.json

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+}

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/CQADupstackUnixRetrieval.json

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results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/ClimateFEVERHardNegatives.json

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results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/FEVERHardNegatives.json

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results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/FiQA2018.json

@@ -0,0 +1,158 @@
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+}

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/HotpotQAHardNegatives.json

@@ -0,0 +1,158 @@
+{
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+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ]
+      }
+    ]
+  },
+  "evaluation_time": 7044.068500757217,
+  "kg_co2_emissions": null
+}

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/ImdbClassification.json

@@ -0,0 +1,95 @@
+{
+  "dataset_revision": "3d86128a09e091d6018b6d26cad27f2739fc2db7",
+  "task_name": "ImdbClassification",
+  "mteb_version": "1.36.26",
+  "scores": {
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+        "f1": 0.886063,
+        "f1_weighted": 0.886063,
+        "ap": 0.832469,
+        "ap_weighted": 0.832469,
+        "scores_per_experiment": [
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+        "hf_subset": "default",
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+          "eng-Latn"
+        ]
+      }
+    ]
+  },
+  "evaluation_time": 285.1492941379547,
+  "kg_co2_emissions": null
+}

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/MTOPDomainClassification.json

@@ -1,7 +1,7 @@
 {
   "dataset_revision": "d80d48c1eb48d3562165c59d59d0034df9fff0bf",
   "task_name": "MTOPDomainClassification",
-  "mteb_version": "1.29.10",
+  "mteb_version": "1.36.26",
   "scores": {
     "validation": [
       {
@@ -129,9 +129,71 @@
         "languages": [
           "deu-Latn"
         ]
+      },
+      {
+        "accuracy": 0.909667,
+        "f1": 0.908085,
+        "f1_weighted": 0.909422,
+        "scores_per_experiment": [
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+          {
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+            "f1_weighted": 0.906515
+          }
+        ],
+        "main_score": 0.909667,
+        "hf_subset": "en",
+        "languages": [
+          "eng-Latn"
+        ]
       }
     ]
   },
-  "evaluation_time": 24.51078462600708,
+  "evaluation_time": 34.160542488098145,
   "kg_co2_emissions": null
 }

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/MassiveIntentClassification.json

@@ -1,7 +1,7 @@
 {
   "dataset_revision": "4672e20407010da34463acc759c162ca9734bca6",
   "task_name": "MassiveIntentClassification",
-  "mteb_version": "1.29.10",
+  "mteb_version": "1.36.26",
   "scores": {
     "validation": [
       {
@@ -62,7 +62,9 @@
         ],
         "main_score": 0.656665,
         "hf_subset": "fa",
-        "languages": ["fas-Arab"]
+        "languages": [
+          "fas-Arab"
+        ]
       },
       {
         "accuracy": 0.644565,
@@ -122,7 +124,9 @@
         ],
         "main_score": 0.644565,
         "hf_subset": "de",
-        "languages": ["deu-Latn"]
+        "languages": [
+          "deu-Latn"
+        ]
       }
     ],
     "test": [
@@ -184,7 +188,9 @@
         ],
         "main_score": 0.653093,
         "hf_subset": "fa",
-        "languages": ["fas-Arab"]
+        "languages": [
+          "fas-Arab"
+        ]
       },
       {
         "accuracy": 0.645931,
@@ -244,10 +250,74 @@
         ],
         "main_score": 0.645931,
         "hf_subset": "de",
-        "languages": ["deu-Latn"]
+        "languages": [
+          "deu-Latn"
+        ]
+      },
+      {
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+        "f1": 0.649946,
+        "f1_weighted": 0.672657,
+        "scores_per_experiment": [
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+          {
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+          {
+            "accuracy": 0.689644,
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+        ],
+        "main_score": 0.680363,
+        "hf_subset": "en",
+        "languages": [
+          "eng-Latn"
+        ]
       }
     ]
   },
-  "evaluation_time": 42.45827603340149,
+  "evaluation_time": 51.4020140171051,
   "kg_co2_emissions": null
 }

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/MassiveScenarioClassification.json

@@ -1,7 +1,7 @@
 {
   "dataset_revision": "fad2c6e8459f9e1c45d9315f4953d921437d70f8",
   "task_name": "MassiveScenarioClassification",
-  "mteb_version": "1.29.10",
+  "mteb_version": "1.36.28",
   "scores": {
     "validation": [
       {
@@ -253,9 +253,71 @@
         "languages": [
           "deu-Latn"
         ]
+      },
+      {
+        "accuracy": 0.717754,
+        "f1": 0.708215,
+        "f1_weighted": 0.712128,
+        "scores_per_experiment": [
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+          {
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+        "main_score": 0.717754,
+        "hf_subset": "en",
+        "languages": [
+          "eng-Latn"
+        ]
       }
     ]
   },
-  "evaluation_time": 24.342835426330566,
+  "evaluation_time": 35.0194628238678,
   "kg_co2_emissions": null
 }

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/MindSmallReranking.json

@@ -0,0 +1,26 @@
+{
+  "dataset_revision": "59042f120c80e8afa9cdbb224f67076cec0fc9a7",
+  "task_name": "MindSmallReranking",
+  "mteb_version": "1.36.28",
+  "scores": {
+    "test": [
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+        "nAUC_mrr_max": -0.19284,
+        "nAUC_mrr_std": -0.04597,
+        "nAUC_mrr_diff1": 0.107977,
+        "main_score": 0.302421,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ]
+      }
+    ]
+  },
+  "evaluation_time": 314.8705949783325,
+  "kg_co2_emissions": null
+}

results/intfloat__multilingual-e5-large/ab10c1a7f42e74530fe7ae5be82e6d4f11a719eb/model_meta.json

@@ -1 +1 @@
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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/AILACasedocs.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/AILAStatutes.json

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+        "nauc_mrr_at_100_std": 0.297155,
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+        "nauc_mrr_at_1000_diff1": 0.175968,
+        "main_score": 0.19011,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ]
+      }
+    ]
+  },
+  "evaluation_time": 0.8368701934814453,
+  "kg_co2_emissions": null
+}

results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/AmazonCounterfactualClassification.json

@@ -1,7 +1,7 @@
 {
   "dataset_revision": "e8379541af4e31359cca9fbcf4b00f2671dba205",
   "task_name": "AmazonCounterfactualClassification",
-  "mteb_version": "1.29.10",
+  "mteb_version": "1.36.26",
   "scores": {
     "validation": [
       {
@@ -173,9 +173,93 @@
         "languages": [
           "deu-Latn"
         ]
+      },
+      {
+        "accuracy": 0.714328,
+        "f1": 0.657781,
+        "f1_weighted": 0.742146,
+        "ap": 0.348333,
+        "ap_weighted": 0.348333,
+        "scores_per_experiment": [
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+            "ap_weighted": 0.337294
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+            "ap_weighted": 0.310545
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+            "ap_weighted": 0.315057
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+        "hf_subset": "en",
+        "languages": [
+          "eng-Latn"
+        ]
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     ]
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-  "evaluation_time": 85.73426079750061,
+  "evaluation_time": 89.0959222316742,
   "kg_co2_emissions": null
 }

results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/AmazonPolarityClassification.json

@@ -0,0 +1,95 @@
+{
+  "dataset_revision": "e2d317d38cd51312af73b3d32a06d1a08b442046",
+  "task_name": "AmazonPolarityClassification",
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+  "scores": {
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+        "f1": 0.87354,
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+        "ap_weighted": 0.836866,
+        "scores_per_experiment": [
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+        "hf_subset": "default",
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+          "eng-Latn"
+        ]
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+  "evaluation_time": 261.6263530254364,
+  "kg_co2_emissions": null
+}

results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/AmazonReviewsClassification.json

@@ -1,7 +1,7 @@
 {
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   "task_name": "AmazonReviewsClassification",
-  "mteb_version": "1.29.10",
+  "mteb_version": "1.36.26",
   "scores": {
     "validation": [
       {
@@ -129,9 +129,71 @@
         "languages": [
           "deu-Latn"
         ]
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   "kg_co2_emissions": null
 }

results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/AngryTweetsClassification.json

@@ -0,0 +1,73 @@
+{
+  "dataset_revision": "20b0e6081892e78179356fada741b7afa381443d",
+  "task_name": "AngryTweetsClassification",
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+}

results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/ArXivHierarchicalClusteringP2P.json

@@ -0,0 +1,46 @@
+{
+  "dataset_revision": "0bbdb47bcbe3a90093699aefeed338a0f28a7ee8",
+  "task_name": "ArXivHierarchicalClusteringP2P",
+  "mteb_version": "1.36.26",
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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/ArXivHierarchicalClusteringS2S.json

@@ -0,0 +1,46 @@
+{
+  "dataset_revision": "b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3",
+  "task_name": "ArXivHierarchicalClusteringS2S",
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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/ArguAna.json

@@ -0,0 +1,158 @@
+{
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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/ArxivClusteringP2P.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/ArxivClusteringS2S.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/AskUbuntuDupQuestions.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/BIOSSES.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/BUCC.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/Banking77Classification.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/BiorxivClusteringP2P.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/BiorxivClusteringP2P.v2.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/BiorxivClusteringS2S.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/BornholmBitextMining.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/CQADupstackAndroidRetrieval.json

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+}

results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/CQADupstackEnglishRetrieval.json

@@ -0,0 +1,158 @@
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+}

results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/CQADupstackGamingRetrieval.json

@@ -0,0 +1,158 @@
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+}

results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/CQADupstackGisRetrieval.json

@@ -0,0 +1,158 @@
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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/CQADupstackMathematicaRetrieval.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/CQADupstackPhysicsRetrieval.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/CQADupstackProgrammersRetrieval.json

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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/CQADupstackRetrieval.json

@@ -0,0 +1,19 @@
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results/intfloat__multilingual-e5-small/fd1525a9fd15316a2d503bf26ab031a61d056e98/CQADupstackStatsRetrieval.json

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