Repository: embeddings-benchmark/mteb (language: python)

Issue:
[mieb] google/siglip-large-patch16-384 fails on ImageNet10Clustering
```
ERROR:mteb.evaluation.MTEB:Error while evaluating ImageNet10Clustering: mean must have 1 elements if it is an iterable, got 3
Traceback (most recent call last):
  File "/data/niklas/mieb/mteb/scripts/run_mieb.py", line 91, in <module>
    results = evaluation.run(model, output_folder="/data/niklas/mieb/results-mieb-final", batch_size=32)
  File "/data/niklas/mieb/mteb/mteb/evaluation/MTEB.py", line 464, in run
    raise e
  File "/data/niklas/mieb/mteb/mteb/evaluation/MTEB.py", line 425, in run
    results, tick, tock = self._run_eval(
  File "/data/niklas/mieb/mteb/mteb/evaluation/MTEB.py", line 300, in _run_eval
    results = task.evaluate(
  File "/data/niklas/mieb/mteb/mteb/abstasks/AbsTask.py", line 126, in evaluate
    scores[hf_subset] = self._evaluate_subset(
  File "/data/niklas/mieb/mteb/mteb/abstasks/Image/AbsTaskImageClustering.py", line 54, in _evaluate_subset
    metrics = evaluator(model, encode_kwargs=encode_kwargs)
  File "/data/niklas/mieb/mteb/mteb/evaluation/evaluators/Image/ClusteringEvaluator.py", line 41, in __call__
    image_embeddings = model.get_image_embeddings(
  File "/data/niklas/mieb/mteb/mteb/models/siglip_models.py", line 74, in get_image_embeddings
    inputs = self.processor(
  File "/env/lib/conda/gritkto4/lib/python3.10/site-packages/transformers/models/siglip/processing_siglip.py", line 113, in __call__
    image_features = self.image_processor(images, return_tensors=return_tensors)
  File "/env/lib/conda/gritkto4/lib/python3.10/site-packages/transformers/image_processing_utils.py", line 41, in __call__
    return self.preprocess(images, **kwargs)
  File "/env/lib/conda/gritkto4/lib/python3.10/site-packages/transformers/utils/generic.py", line 852, in wrapper
    return func(*args, **valid_kwargs)
  File "/env/lib/conda/gritkto4/lib/python3.10/site-packages/transformers/models/siglip/image_processing_siglip.py", line 231, in preprocess
    images = [
  File "/env/lib/conda/gritkto4/lib/python3.10/site-packages/transformers/models/siglip/image_processing_siglip.py", line 232, in <listcomp>
    self.normalize(image=image, mean=image_mean, std=image_std, input_data_format=input_data_format)
  File "/env/lib/conda/gritkto4/lib/python3.10/site-packages/transformers/image_processing_utils.py", line 111, in normalize
    return normalize(
  File "/env/lib/conda/gritkto4/lib/python3.10/site-packages/transformers/image_transforms.py", line 398, in normalize
    raise ValueError(f"mean must have {num_channels} elements if it is an iterable, got {len(mean)}")
ValueError: mean must have 1 elements if it is an iterable, got 3

```


Discussion / hints:

Fix patch:
diff --git a/mteb/models/siglip_models.py b/mteb/models/siglip_models.py
index 17e7dd0056..3c33139920 100644
--- a/mteb/models/siglip_models.py
+++ b/mteb/models/siglip_models.py
@@ -40,11 +40,13 @@ def get_text_embeddings(self, texts: list[str], batch_size: int = 32):
             for i in tqdm(range(0, len(texts), batch_size)):
                 batch_texts = texts[i : i + batch_size]
                 inputs = self.processor(
-                    text=batch_texts, return_tensors="pt", padding=True, truncation=True
+                    text=batch_texts,
+                    return_tensors="pt",
+                    padding="max_length",
+                    truncation=True,
                 )
                 inputs = {k: v.to(self.device) for k, v in inputs.items()}
                 text_outputs = self.model.get_text_features(**inputs)
-                text_outputs = text_outputs / text_outputs.norm(dim=-1, keepdim=True)
                 all_text_embeddings.append(text_outputs.cpu())
 
         all_text_embeddings = torch.cat(all_text_embeddings, dim=0)
@@ -63,22 +65,22 @@ def get_image_embeddings(
                     )
                     inputs = {k: v.to(self.device) for k, v in inputs.items()}
                     image_outputs = self.model.get_image_features(**inputs)
-                    image_outputs = image_outputs / image_outputs.norm(
-                        dim=-1, keepdim=True
-                    )
                     all_image_embeddings.append(image_outputs.cpu())
         else:
             with torch.no_grad():
                 for i in tqdm(range(0, len(images), batch_size)):
                     batch_images = images[i : i + batch_size]
+                    batch_images = [
+                        img.convert("RGB")
+                        if isinstance(img, Image.Image) and img.mode != "RGB"
+                        else img
+                        for img in batch_images
+                    ]
                     inputs = self.processor(
                         images=batch_images, return_tensors="pt", padding=True
                     )
                     inputs = {k: v.to(self.device) for k, v in inputs.items()}
                     image_outputs = self.model.get_image_features(**inputs)
-                    image_outputs = image_outputs / image_outputs.norm(
-                        dim=-1, keepdim=True
-                    )
                     all_image_embeddings.append(image_outputs.cpu())
 
         all_image_embeddings = torch.cat(all_image_embeddings, dim=0)
diff --git a/mteb/tasks/Image/Any2AnyRetrieval/__init__.py b/mteb/tasks/Image/Any2AnyRetrieval/__init__.py
index d4822a3473..59fbb1a11a 100644
--- a/mteb/tasks/Image/Any2AnyRetrieval/__init__.py
+++ b/mteb/tasks/Image/Any2AnyRetrieval/__init__.py
@@ -4,12 +4,14 @@
 from .eng.BLINKIT2TRetrieval import *
 from .eng.CIRRIT2IRetrieval import *
 from .eng.CUB200I2IRetrieval import *
+from .eng.EDIST2ITRetrieval import *
 from .eng.Fashion200kI2TRetrieval import *
 from .eng.Fashion200kT2IRetrieval import *
 from .eng.FashionIQIT2IRetrieval import *
 from .eng.Flickr30kI2TRetrieval import *
 from .eng.Flickr30kT2IRetrieval import *
 from .eng.FORBI2IRetrieval import *
+from .eng.GLDv2I2IRetrieval import *
 from .eng.GLDv2I2TRetrieval import *
 from .eng.HatefulMemesI2TRetrieval import *
 from .eng.HatefulMemesT2IRetrieval import *
diff --git a/mteb/tasks/Image/Any2AnyRetrieval/eng/EDIST2ITRetrieval.py b/mteb/tasks/Image/Any2AnyRetrieval/eng/EDIST2ITRetrieval.py
new file mode 100644
index 0000000000..e1f8309066
--- /dev/null
+++ b/mteb/tasks/Image/Any2AnyRetrieval/eng/EDIST2ITRetrieval.py
@@ -0,0 +1,48 @@
+from __future__ import annotations
+
+from mteb.abstasks.Image.AbsTaskAny2AnyRetrieval import AbsTaskAny2AnyRetrieval
+from mteb.abstasks.TaskMetadata import TaskMetadata
+
+
+class EDIST2ITRetrieval(AbsTaskAny2AnyRetrieval):
+    metadata = TaskMetadata(
+        name="EDIST2ITRetrieval",
+        description="Retrieve news images and titles based on news content.",
+        reference="https://aclanthology.org/2023.emnlp-main.297/",
+        dataset={
+            "path": "MRBench/mbeir_edis_task2",
+            "revision": "68c47ef3e49ef883073b3358bd4243eeca0aee9a",
+        },
+        type="Any2AnyRetrieval",
+        category="t2it",
+        eval_splits=["test"],
+        eval_langs=["eng-Latn"],
+        main_score="ndcg_at_10",
+        date=("2023-01-01", "2023-12-31"),
+        domains=["News"],
+        task_subtypes=["Image Text Retrieval"],
+        license="apache-2.0",
+        annotations_creators="derived",
+        dialect=[],
+        modalities=["text", "image"],
+        sample_creation="created",
+        bibtex_citation="""@inproceedings{liu2023edis,
+  title={EDIS: Entity-Driven Image Search over Multimodal Web Content},
+  author={Liu, Siqi and Feng, Weixi and Fu, Tsu-Jui and Chen, Wenhu and Wang, William},
+  booktitle={Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing},
+  pages={4877--4894},
+  year={2023}
+}""",
+        descriptive_stats={
+            "n_samples": {"test": 3241},
+            "avg_character_length": {
+                "test": {
+                    "average_document_length": 0.0,
+                    "average_query_length": 0.0,
+                    "num_documents": 1047067,
+                    "num_queries": 3241,
+                    "average_relevant_docs_per_query": 2.57,
+                }
+            },
+        },
+    )
diff --git a/mteb/tasks/Image/Any2AnyRetrieval/eng/GLDv2I2IRetrieval.py b/mteb/tasks/Image/Any2AnyRetrieval/eng/GLDv2I2IRetrieval.py
new file mode 100644
index 0000000000..1d0c2c3bcf
--- /dev/null
+++ b/mteb/tasks/Image/Any2AnyRetrieval/eng/GLDv2I2IRetrieval.py
@@ -0,0 +1,50 @@
+from __future__ import annotations
+
+from mteb.abstasks.Image.AbsTaskAny2AnyRetrieval import AbsTaskAny2AnyRetrieval
+from mteb.abstasks.TaskMetadata import TaskMetadata
+
+
+class GLDv2I2IRetrieval(AbsTaskAny2AnyRetrieval):
+    metadata = TaskMetadata(
+        name="GLDv2I2IRetrieval",
+        description="Retrieve names of landmarks based on their image.",
+        reference="https://openaccess.thecvf.com/content_CVPR_2020/html/Weyand_Google_Landmarks_Dataset_v2_-_A_Large-Scale_Benchmark_for_Instance-Level_CVPR_2020_paper.html",
+        dataset={
+            "path": "gowitheflow/gld-v2",
+            "revision": "c6b162ee349adb293901128a18c0b446f7b43457",
+        },
+        type="Any2AnyRetrieval",
+        category="i2i",
+        eval_splits=["test"],
+        eval_langs=["eng-Latn"],
+        main_score="ndcg_at_10",
+        date=("2017-01-01", "2017-12-31"),
+        domains=["Encyclopaedic"],
+        task_subtypes=["Image Text Retrieval"],
+        license="apache-2.0",
+        annotations_creators="derived",
+        dialect=[],
+        modalities=["image"],
+        sample_creation="created",
+        bibtex_citation="""@InProceedings{Weyand_2020_CVPR,
+author = {Weyand, Tobias and Araujo, Andre and Cao, Bingyi and Sim, Jack},
+title = {Google Landmarks Dataset v2 - A Large-Scale Benchmark for Instance-Level Recognition and Retrieval},
+booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+month = {June},
+year = {2020}
+}
+
+""",
+        descriptive_stats={
+            "n_samples": {"test": 1129},
+            "avg_character_length": {
+                "test": {
+                    "average_document_length": 0.0,
+                    "average_query_length": 0.0,
+                    "num_documents": 847728,
+                    "num_queries": 1129,
+                    "average_relevant_docs_per_query": 13.49,
+                }
+            },
+        },
+    )
diff --git a/results-mieb/facebook__dinov2-small/ed25f3a31f01632728cabb09d1542f84ab7b0056/GLDv2I2IRetrieval.json b/results-mieb/facebook__dinov2-small/ed25f3a31f01632728cabb09d1542f84ab7b0056/GLDv2I2IRetrieval.json
new file mode 100644
index 0000000000..2ce64ec37b
--- /dev/null
+++ b/results-mieb/facebook__dinov2-small/ed25f3a31f01632728cabb09d1542f84ab7b0056/GLDv2I2IRetrieval.json
@@ -0,0 +1,186 @@
+{
+  "dataset_revision": "c6b162ee349adb293901128a18c0b446f7b43457",
+  "evaluation_time": 4408.689854860306,
+  "kg_co2_emissions": null,
+  "mteb_version": "1.14.15",
+  "scores": {
+    "test": [
+      {
+        "cv_recall_at_1": 0.4535,
+        "cv_recall_at_10": 0.57219,
+        "cv_recall_at_100": 0.6519,
+        "cv_recall_at_1000": 0.73339,
+        "cv_recall_at_20": 0.59433,
+        "cv_recall_at_3": 0.50753,
+        "cv_recall_at_5": 0.5403,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ],
+        "main_score": 0.28941,
+        "map_at_1": 0.05847,
+        "map_at_10": 0.15245,
+        "map_at_100": 0.17257,
+        "map_at_1000": 0.1746,
+        "map_at_20": 0.16358,
+        "map_at_3": 0.10746,
+        "map_at_5": 0.1285,
+        "mrr_at_1": 0.4534986713906112,
+        "mrr_at_10": 0.48867237476626324,
+        "mrr_at_100": 0.4915899189723126,
+        "mrr_at_1000": 0.49191288914802445,
+        "mrr_at_20": 0.4902356580948968,
+        "mrr_at_3": 0.4769707705934455,
+        "mrr_at_5": 0.48436669619131967,
+        "nauc_cv_recall_at_1000_diff1": 0.34148107488406604,
+        "nauc_cv_recall_at_1000_max": 0.5657029091377153,
+        "nauc_cv_recall_at_1000_std": 0.3365411347443642,
+        "nauc_cv_recall_at_100_diff1": 0.3808148655813085,
+        "nauc_cv_recall_at_100_max": 0.5494694185142655,
+        "nauc_cv_recall_at_100_std": 0.2927349479831974,
+        "nauc_cv_recall_at_10_diff1": 0.40118856921921564,
+        "nauc_cv_recall_at_10_max": 0.5702709786136617,
+        "nauc_cv_recall_at_10_std": 0.2506097969647151,
+        "nauc_cv_recall_at_1_diff1": 0.43232239408517925,
+        "nauc_cv_recall_at_1_max": 0.6111730350701059,
+        "nauc_cv_recall_at_1_std": 0.2626457116510796,
+        "nauc_cv_recall_at_20_diff1": 0.3976444877640721,
+        "nauc_cv_recall_at_20_max": 0.5561717117356078,
+        "nauc_cv_recall_at_20_std": 0.258312177592681,
+        "nauc_cv_recall_at_3_diff1": 0.4162409238600696,
+        "nauc_cv_recall_at_3_max": 0.5731658448651727,
+        "nauc_cv_recall_at_3_std": 0.24259357095035114,
+        "nauc_cv_recall_at_5_diff1": 0.40222757559525246,
+        "nauc_cv_recall_at_5_max": 0.5740443308429867,
+        "nauc_cv_recall_at_5_std": 0.2638681693812113,
+        "nauc_map_at_1000_diff1": 0.18861481679640155,
+        "nauc_map_at_1000_max": 0.49541010487450027,
+        "nauc_map_at_1000_std": 0.25479149329445355,
+        "nauc_map_at_100_diff1": 0.19036469102447715,
+        "nauc_map_at_100_max": 0.49424236992956605,
+        "nauc_map_at_100_std": 0.2508171110383186,
+        "nauc_map_at_10_diff1": 0.22996775077271184,
+        "nauc_map_at_10_max": 0.4659523068740507,
+        "nauc_map_at_10_std": 0.17873558257018604,
+        "nauc_map_at_1_diff1": 0.4814554391164708,
+        "nauc_map_at_1_max": 0.22663592739850807,
+        "nauc_map_at_1_std": -0.016374913627465144,
+        "nauc_map_at_20_diff1": 0.20523019715428878,
+        "nauc_map_at_20_max": 0.48572148693290934,
+        "nauc_map_at_20_std": 0.21802056174164897,
+        "nauc_map_at_3_diff1": 0.3578012044738236,
+        "nauc_map_at_3_max": 0.35368283917955673,
+        "nauc_map_at_3_std": 0.07546794596340074,
+        "nauc_map_at_5_diff1": 0.2966436966851955,
+        "nauc_map_at_5_max": 0.4113893523345609,
+        "nauc_map_at_5_std": 0.12432827131997834,
+        "nauc_mrr_at_1000_diff1": 0.4219354542268342,
+        "nauc_mrr_at_1000_max": 0.5938517870610833,
+        "nauc_mrr_at_1000_std": 0.25789989416553666,
+        "nauc_mrr_at_100_diff1": 0.42195820028912456,
+        "nauc_mrr_at_100_max": 0.5938569414601591,
+        "nauc_mrr_at_100_std": 0.25780053121453195,
+        "nauc_mrr_at_10_diff1": 0.4226196920315362,
+        "nauc_mrr_at_10_max": 0.5949390240575794,
+        "nauc_mrr_at_10_std": 0.2568484636479838,
+        "nauc_mrr_at_1_diff1": 0.43232239408517925,
+        "nauc_mrr_at_1_max": 0.6111730350701059,
+        "nauc_mrr_at_1_std": 0.2626457116510796,
+        "nauc_mrr_at_20_diff1": 0.4223978068861933,
+        "nauc_mrr_at_20_max": 0.59408807498729,
+        "nauc_mrr_at_20_std": 0.2573461830046759,
+        "nauc_mrr_at_3_diff1": 0.4262502276324796,
+        "nauc_mrr_at_3_max": 0.5954118493110601,
+        "nauc_mrr_at_3_std": 0.2545125910785488,
+        "nauc_mrr_at_5_diff1": 0.4228118558706074,
+        "nauc_mrr_at_5_max": 0.5953723133930325,
+        "nauc_mrr_at_5_std": 0.25854738381668874,
+        "nauc_ndcg_at_1000_diff1": 0.22343292588387825,
+        "nauc_ndcg_at_1000_max": 0.5276606021449388,
+        "nauc_ndcg_at_1000_std": 0.29728763467934904,
+        "nauc_ndcg_at_100_diff1": 0.23190304701399703,
+        "nauc_ndcg_at_100_max": 0.5245071773764476,
+        "nauc_ndcg_at_100_std": 0.2783843293138034,
+        "nauc_ndcg_at_10_diff1": 0.19316555007961791,
+        "nauc_ndcg_at_10_max": 0.5825075587136279,
+        "nauc_ndcg_at_10_std": 0.3092465370973502,
+        "nauc_ndcg_at_1_diff1": 0.43232239408517925,
+        "nauc_ndcg_at_1_max": 0.6111730350701059,
+        "nauc_ndcg_at_1_std": 0.2626457116510796,
+        "nauc_ndcg_at_20_diff1": 0.21755951662398187,
+        "nauc_ndcg_at_20_max": 0.5475682374017373,
+        "nauc_ndcg_at_20_std": 0.2860733738075765,
+        "nauc_ndcg_at_3_diff1": 0.24971063630292664,
+        "nauc_ndcg_at_3_max": 0.6086291585528392,
+        "nauc_ndcg_at_3_std": 0.2992078517726314,
+        "nauc_ndcg_at_5_diff1": 0.21400973879521373,
+        "nauc_ndcg_at_5_max": 0.605819692716699,
+        "nauc_ndcg_at_5_std": 0.31456299770488383,
+        "nauc_precision_at_1000_diff1": -0.044719214820325454,
+        "nauc_precision_at_1000_max": 0.469245361680825,
+        "nauc_precision_at_1000_std": 0.459126550464243,
+        "nauc_precision_at_100_diff1": -0.0361873993762923,
+        "nauc_precision_at_100_max": 0.5372410748582264,
+        "nauc_precision_at_100_std": 0.49655377124356126,
+        "nauc_precision_at_10_diff1": 0.02048413751839119,
+        "nauc_precision_at_10_max": 0.601718588539165,
+        "nauc_precision_at_10_std": 0.38924805371157156,
+        "nauc_precision_at_1_diff1": 0.43232239408517925,
+        "nauc_precision_at_1_max": 0.6111730350701059,
+        "nauc_precision_at_1_std": 0.2626457116510796,
+        "nauc_precision_at_20_diff1": -0.01598332604841292,
+        "nauc_precision_at_20_max": 0.5860681313676941,
+        "nauc_precision_at_20_std": 0.4447422992419558,
+        "nauc_precision_at_3_diff1": 0.18237525035807778,
+        "nauc_precision_at_3_max": 0.6073405177582907,
+        "nauc_precision_at_3_std": 0.3148368780578123,
+        "nauc_precision_at_5_diff1": 0.10080092161444594,
+        "nauc_precision_at_5_max": 0.6113824415227623,
+        "nauc_precision_at_5_std": 0.3542916057954643,
+        "nauc_recall_at_1000_diff1": 0.11156694655914166,
+        "nauc_recall_at_1000_max": 0.4029532703125521,
+        "nauc_recall_at_1000_std": 0.3191218466863474,
+        "nauc_recall_at_100_diff1": 0.15346884478259795,
+        "nauc_recall_at_100_max": 0.4263756821168572,
+        "nauc_recall_at_100_std": 0.2667922963100197,
+        "nauc_recall_at_10_diff1": 0.20481260563318826,
+        "nauc_recall_at_10_max": 0.42307599013145597,
+        "nauc_recall_at_10_std": 0.16281281054955174,
+        "nauc_recall_at_1_diff1": 0.4814554391164708,
+        "nauc_recall_at_1_max": 0.22663592739850807,
+        "nauc_recall_at_1_std": -0.016374913627465144,
+        "nauc_recall_at_20_diff1": 0.1805511540924871,
+        "nauc_recall_at_20_max": 0.4341772622005704,
+        "nauc_recall_at_20_std": 0.20225716907182484,
+        "nauc_recall_at_3_diff1": 0.343757341612119,
+        "nauc_recall_at_3_max": 0.33208304495011726,
+        "nauc_recall_at_3_std": 0.0633600297459121,
+        "nauc_recall_at_5_diff1": 0.2784926120476109,
+        "nauc_recall_at_5_max": 0.3814328242345907,
+        "nauc_recall_at_5_std": 0.11379188945081205,
+        "ndcg_at_1": 0.4535,
+        "ndcg_at_10": 0.28941,
+        "ndcg_at_100": 0.26716,
+        "ndcg_at_1000": 0.29187,
+        "ndcg_at_20": 0.26099,
+        "ndcg_at_3": 0.37311,
+        "ndcg_at_5": 0.33283,
+        "precision_at_1": 0.4535,
+        "precision_at_10": 0.19699,
+        "precision_at_100": 0.03368,
+        "precision_at_1000": 0.00467,
+        "precision_at_20": 0.12161,
+        "precision_at_3": 0.34485,
+        "precision_at_5": 0.28131,
+        "recall_at_1": 0.05847,
+        "recall_at_10": 0.17682,
+        "recall_at_100": 0.25581,
+        "recall_at_1000": 0.34658,
+        "recall_at_20": 0.20188,
+        "recall_at_3": 0.11247,
+        "recall_at_5": 0.13964
+      }
+    ]
+  },
+  "task_name": "GLDv2I2IRetrieval"
+}
\ No newline at end of file
diff --git a/results-mieb/google__siglip-base-patch16-256/b078df89e446d623010d890864d4207fe6399f61/CIFAR10.json b/results-mieb/google__siglip-base-patch16-256/b078df89e446d623010d890864d4207fe6399f61/CIFAR10.json
new file mode 100644
index 0000000000..a94a3ac8a1
--- /dev/null
+++ b/results-mieb/google__siglip-base-patch16-256/b078df89e446d623010d890864d4207fe6399f61/CIFAR10.json
@@ -0,0 +1,48 @@
+{
+  "dataset_revision": "0b2714987fa478483af9968de7c934580d0bb9a2",
+  "evaluation_time": 59.87628698348999,
+  "kg_co2_emissions": null,
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+  "scores": {
+    "test": [
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+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ],
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+        "scores_per_experiment": [
+          {
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+            "f1": 0.9325960933629046,
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+            "f1_weighted": 0.9363950655467698
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+        ]
+      }
+    ]
+  },
+  "task_name": "CIFAR10"
+}
\ No newline at end of file
diff --git a/results-mieb/google__siglip-base-patch16-256/b078df89e446d623010d890864d4207fe6399f61/CIFAR100.json b/results-mieb/google__siglip-base-patch16-256/b078df89e446d623010d890864d4207fe6399f61/CIFAR100.json
new file mode 100644
index 0000000000..f7b2bb3c5c
--- /dev/null
+++ b/results-mieb/google__siglip-base-patch16-256/b078df89e446d623010d890864d4207fe6399f61/CIFAR100.json
@@ -0,0 +1,48 @@
+{
+  "dataset_revision": "aadb3af77e9048adbea6b47c21a81e47dd092ae5",
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+            "f1_weighted": 0.7598610206997176
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+        ]
+      }
+    ]
+  },
+  "task_name": "CIFAR100"
+}
\ No newline at end of file
diff --git a/results-mieb/google__siglip-base-patch16-256/b078df89e446d623010d890864d4207fe6399f61/MNIST.json b/results-mieb/google__siglip-base-patch16-256/b078df89e446d623010d890864d4207fe6399f61/MNIST.json
new file mode 100644
index 0000000000..5c6ed62858
--- /dev/null
+++ b/results-mieb/google__siglip-base-patch16-256/b078df89e446d623010d890864d4207fe6399f61/MNIST.json
@@ -0,0 +1,48 @@
+{
+  "dataset_revision": "77f3279092a1c1579b2250db8eafed0ad422088c",
+  "evaluation_time": 56.67082715034485,
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+      }
+    ]
+  },
+  "task_name": "MNIST"
+}
\ No newline at end of file
diff --git a/results-mieb/google__siglip-base-patch16-256/b078df89e446d623010d890864d4207fe6399f61/MNISTZeroShot.json b/results-mieb/google__siglip-base-patch16-256/b078df89e446d623010d890864d4207fe6399f61/MNISTZeroShot.json
new file mode 100644
index 0000000000..b77069c7c0
--- /dev/null
+++ b/results-mieb/google__siglip-base-patch16-256/b078df89e446d623010d890864d4207fe6399f61/MNISTZeroShot.json
@@ -0,0 +1,19 @@
+{
+  "dataset_revision": "77f3279092a1c1579b2250db8eafed0ad422088c",
+  "evaluation_time": 50.64418292045593,
+  "kg_co2_emissions": null,
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+        "languages": [
+          "eng-Latn"
+        ],
+        "main_score": 0.8457
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+    ]
+  },
+  "task_name": "MNISTZeroShot"
+}
\ No newline at end of file
diff --git a/results-mieb/google__siglip-large-patch16-384/ce005573a40965dfd21fd937fbdeeebf2439fc35/ImageNet10Clustering.json b/results-mieb/google__siglip-large-patch16-384/ce005573a40965dfd21fd937fbdeeebf2439fc35/ImageNet10Clustering.json
new file mode 100644
index 0000000000..185e72dbf7
--- /dev/null
+++ b/results-mieb/google__siglip-large-patch16-384/ce005573a40965dfd21fd937fbdeeebf2439fc35/ImageNet10Clustering.json
@@ -0,0 +1,22 @@
+{
+  "dataset_revision": "88f8a6d47c257895094c5ad81e67ba751771fc99",
+  "evaluation_time": 408.774094581604,
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+  "scores": {
+    "test": [
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+        "nmi": 0.9806773175345154,
+        "v_measure": 0.9806773175345154
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+    ]
+  },
+  "task_name": "ImageNet10Clustering"
+}
\ No newline at end of file
diff --git a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreArxivQARetrieval.json b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreArxivQARetrieval.json
index eeaf17e01d..6c5b4b0d05 100644
--- a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreArxivQARetrieval.json
+++ b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreArxivQARetrieval.json
@@ -1,184 +1,184 @@
 {
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diff --git a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreDocVQARetrieval.json b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreDocVQARetrieval.json
index 2ba30bc4d6..53c2fdfc97 100644
--- a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreDocVQARetrieval.json
+++ b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreDocVQARetrieval.json
@@ -1,184 +1,184 @@
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diff --git a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreInfoVQARetrieval.json b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreInfoVQARetrieval.json
index aea7cf6a30..031ebfff4e 100644
--- a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreInfoVQARetrieval.json
+++ b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreInfoVQARetrieval.json
@@ -1,184 +1,184 @@
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diff --git a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreShiftProjectRetrieval.json b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreShiftProjectRetrieval.json
index b417221b6f..374bde6d4e 100644
--- a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreShiftProjectRetrieval.json
+++ b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreShiftProjectRetrieval.json
@@ -1,6 +1,6 @@
 {
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diff --git a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAAIRetrieval.json b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAAIRetrieval.json
index 057976d0ba..1836f819bb 100644
--- a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAAIRetrieval.json
+++ b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAAIRetrieval.json
@@ -1,184 +1,184 @@
 {
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diff --git a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAEnergyRetrieval.json b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAEnergyRetrieval.json
index 62f44290d2..d2071daf29 100644
--- a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAEnergyRetrieval.json
+++ b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAEnergyRetrieval.json
@@ -1,184 +1,184 @@
 {
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diff --git a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAGovernmentReportsRetrieval.json b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAGovernmentReportsRetrieval.json
index c0bd444fb8..1c60fce707 100644
--- a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAGovernmentReportsRetrieval.json
+++ b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAGovernmentReportsRetrieval.json
@@ -1,184 +1,184 @@
 {
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diff --git a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAHealthcareIndustryRetrieval.json b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAHealthcareIndustryRetrieval.json
index f80c15a971..3828955dfa 100644
--- a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAHealthcareIndustryRetrieval.json
+++ b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreSyntheticDocQAHealthcareIndustryRetrieval.json
@@ -1,184 +1,184 @@
 {
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diff --git a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreTabfquadRetrieval.json b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreTabfquadRetrieval.json
index 85526aa435..817d0b4849 100644
--- a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreTabfquadRetrieval.json
+++ b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreTabfquadRetrieval.json
@@ -1,184 +1,184 @@
 {
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diff --git a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreTatdqaRetrieval.json b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreTatdqaRetrieval.json
index 29032ce4c6..9aa82d28ab 100644
--- a/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreTatdqaRetrieval.json
+++ b/results-mieb/google__siglip-so400m-patch14-384/9fdffc58afc957d1a03a25b10dba0329ab15c2a3/VidoreTatdqaRetrieval.json
@@ -1,184 +1,184 @@
 {
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diff --git a/results-mieb/openai__clip-vit-base-patch32/3d74acf9a28c67741b2f4f2ea7635f0aaf6f0268/EDIST2ITRetrieval.json b/results-mieb/openai__clip-vit-base-patch32/3d74acf9a28c67741b2f4f2ea7635f0aaf6f0268/EDIST2ITRetrieval.json
new file mode 100644
index 0000000000..b8c457c9ae
--- /dev/null
+++ b/results-mieb/openai__clip-vit-base-patch32/3d74acf9a28c67741b2f4f2ea7635f0aaf6f0268/EDIST2ITRetrieval.json
@@ -0,0 +1,186 @@
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+      }
+    ]
+  },
+  "task_name": "EDIST2ITRetrieval"
+}
\ No newline at end of file
diff --git a/results-mieb/openai__clip-vit-base-patch32/3d74acf9a28c67741b2f4f2ea7635f0aaf6f0268/GLDv2I2IRetrieval.json b/results-mieb/openai__clip-vit-base-patch32/3d74acf9a28c67741b2f4f2ea7635f0aaf6f0268/GLDv2I2IRetrieval.json
new file mode 100644
index 0000000000..cd8dcc6a44
--- /dev/null
+++ b/results-mieb/openai__clip-vit-base-patch32/3d74acf9a28c67741b2f4f2ea7635f0aaf6f0268/GLDv2I2IRetrieval.json
@@ -0,0 +1,186 @@
+{
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+        "ndcg_at_1": 0.23206,
+        "ndcg_at_10": 0.15119,
+        "ndcg_at_100": 0.15473,
+        "ndcg_at_1000": 0.18542,
+        "ndcg_at_20": 0.14062,
+        "ndcg_at_3": 0.19526,
+        "ndcg_at_5": 0.17429,
+        "precision_at_1": 0.23206,
+        "precision_at_10": 0.11001,
+        "precision_at_100": 0.02504,
+        "precision_at_1000": 0.00415,
+        "precision_at_20": 0.07516,
+        "precision_at_3": 0.18364,
+        "precision_at_5": 0.15182,
+        "recall_at_1": 0.02397,
+        "recall_at_10": 0.08901,
+        "recall_at_100": 0.17505,
+        "recall_at_1000": 0.28531,
+        "recall_at_20": 0.11334,
+        "recall_at_3": 0.05164,
+        "recall_at_5": 0.06666
+      }
+    ]
+  },
+  "task_name": "GLDv2I2IRetrieval"
+}
\ No newline at end of file


Test patch:
diff --git a/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/CIFAR10.json b/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/CIFAR10.json
new file mode 100644
index 0000000000..328e3b46b4
--- /dev/null
+++ b/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/CIFAR10.json
@@ -0,0 +1,48 @@
+{
+  "dataset_revision": "0b2714987fa478483af9968de7c934580d0bb9a2",
+  "evaluation_time": 48.409629821777344,
+  "kg_co2_emissions": null,
+  "mteb_version": "1.14.15",
+  "scores": {
+    "test": [
+      {
+        "accuracy": 0.92594,
+        "f1": 0.9260547788569216,
+        "f1_weighted": 0.9260547788569216,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ],
+        "main_score": 0.92594,
+        "scores_per_experiment": [
+          {
+            "accuracy": 0.9249,
+            "f1": 0.9250702364213208,
+            "f1_weighted": 0.9250702364213208
+          },
+          {
+            "accuracy": 0.9232,
+            "f1": 0.9231630424362665,
+            "f1_weighted": 0.9231630424362666
+          },
+          {
+            "accuracy": 0.9217,
+            "f1": 0.9218520263643336,
+            "f1_weighted": 0.9218520263643335
+          },
+          {
+            "accuracy": 0.9308,
+            "f1": 0.9308028706566229,
+            "f1_weighted": 0.930802870656623
+          },
+          {
+            "accuracy": 0.9291,
+            "f1": 0.9293857184060645,
+            "f1_weighted": 0.9293857184060643
+          }
+        ]
+      }
+    ]
+  },
+  "task_name": "CIFAR10"
+}
\ No newline at end of file
diff --git a/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/CIFAR100.json b/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/CIFAR100.json
new file mode 100644
index 0000000000..0ef0c4ba83
--- /dev/null
+++ b/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/CIFAR100.json
@@ -0,0 +1,48 @@
+{
+  "dataset_revision": "aadb3af77e9048adbea6b47c21a81e47dd092ae5",
+  "evaluation_time": 82.63413286209106,
+  "kg_co2_emissions": null,
+  "mteb_version": "1.14.15",
+  "scores": {
+    "test": [
+      {
+        "accuracy": 0.7413199999999999,
+        "f1": 0.7440710594068098,
+        "f1_weighted": 0.7440710594068098,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ],
+        "main_score": 0.7413199999999999,
+        "scores_per_experiment": [
+          {
+            "accuracy": 0.7393,
+            "f1": 0.7415575159167781,
+            "f1_weighted": 0.7415575159167781
+          },
+          {
+            "accuracy": 0.7449,
+            "f1": 0.7471305285419396,
+            "f1_weighted": 0.7471305285419396
+          },
+          {
+            "accuracy": 0.7428,
+            "f1": 0.7465020754943685,
+            "f1_weighted": 0.7465020754943685
+          },
+          {
+            "accuracy": 0.7423,
+            "f1": 0.744902146154522,
+            "f1_weighted": 0.7449021461545219
+          },
+          {
+            "accuracy": 0.7373,
+            "f1": 0.7402630309264411,
+            "f1_weighted": 0.7402630309264413
+          }
+        ]
+      }
+    ]
+  },
+  "task_name": "CIFAR100"
+}
\ No newline at end of file
diff --git a/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/ImageNet10Clustering.json b/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/ImageNet10Clustering.json
new file mode 100644
index 0000000000..866c25f1fe
--- /dev/null
+++ b/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/ImageNet10Clustering.json
@@ -0,0 +1,22 @@
+{
+  "dataset_revision": "88f8a6d47c257895094c5ad81e67ba751771fc99",
+  "evaluation_time": 50.5283944606781,
+  "kg_co2_emissions": null,
+  "mteb_version": "1.14.15",
+  "scores": {
+    "test": [
+      {
+        "ari": 0.9791753845317047,
+        "cluster_accuracy": 0.9905384615384616,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ],
+        "main_score": 0.9739308018003532,
+        "nmi": 0.9739308018003532,
+        "v_measure": 0.9739308018003532
+      }
+    ]
+  },
+  "task_name": "ImageNet10Clustering"
+}
\ No newline at end of file
diff --git a/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/MNIST.json b/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/MNIST.json
new file mode 100644
index 0000000000..264a93931c
--- /dev/null
+++ b/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/MNIST.json
@@ -0,0 +1,48 @@
+{
+  "dataset_revision": "77f3279092a1c1579b2250db8eafed0ad422088c",
+  "evaluation_time": 46.19513821601868,
+  "kg_co2_emissions": null,
+  "mteb_version": "1.14.15",
+  "scores": {
+    "test": [
+      {
+        "accuracy": 0.95434,
+        "f1": 0.9542219615719318,
+        "f1_weighted": 0.9544309958560502,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ],
+        "main_score": 0.95434,
+        "scores_per_experiment": [
+          {
+            "accuracy": 0.9543,
+            "f1": 0.9542073639183843,
+            "f1_weighted": 0.9544394896400503
+          },
+          {
+            "accuracy": 0.949,
+            "f1": 0.9487069493447204,
+            "f1_weighted": 0.9489175533097969
+          },
+          {
+            "accuracy": 0.9586,
+            "f1": 0.9583645832273339,
+            "f1_weighted": 0.958733263357083
+          },
+          {
+            "accuracy": 0.9522,
+            "f1": 0.9522190790543403,
+            "f1_weighted": 0.9523957230838139
+          },
+          {
+            "accuracy": 0.9576,
+            "f1": 0.9576118323148799,
+            "f1_weighted": 0.957668949889507
+          }
+        ]
+      }
+    ]
+  },
+  "task_name": "MNIST"
+}
\ No newline at end of file
diff --git a/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/MNISTZeroShot.json b/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/MNISTZeroShot.json
new file mode 100644
index 0000000000..06769b48eb
--- /dev/null
+++ b/results-mieb/google__siglip-base-patch16-224/7fd15f0689c79d79e38b1c2e2e2370a7bf2761ed/MNISTZeroShot.json
@@ -0,0 +1,19 @@
+{
+  "dataset_revision": "77f3279092a1c1579b2250db8eafed0ad422088c",
+  "evaluation_time": 38.23384070396423,
+  "kg_co2_emissions": null,
+  "mteb_version": "1.14.15",
+  "scores": {
+    "test": [
+      {
+        "accuracy": 0.8361,
+        "hf_subset": "default",
+        "languages": [
+          "eng-Latn"
+        ],
+        "main_score": 0.8361
+      }
+    ]
+  },
+  "task_name": "MNISTZeroShot"
+}
\ No newline at end of file