Add dataset card

README.md

@@ -6,9 +6,9 @@ language:
 license: unknown
 multilinguality: monolingual
 source_datasets:
-- HuggingFaceM4/FGVC-Aircraft
+- mteb/FGVCAircraftZeroShot
 task_categories:
-- zero-shot-image-classification
+- zero-shot-classification
 - image-to-text
 - text-to-image
 task_ids: []
@@ -341,12 +341,12 @@ Classifying aircraft images from 41 manufacturers and 102 variants.
 
 |               |                                             |
 |---------------|---------------------------------------------|
-| Task category | i2t                              |
+| Task category | ZeroShotClassification (image-to-text)                              |
 | Domains       | Encyclopaedic                               |
-| Reference     | https://arxiv.org/abs/1306.5151 |
+| Reference     | [Fine-Grained Visual Classification of Aircraft](https://arxiv.org/abs/1306.5151) |
 
 Source datasets:
-- [HuggingFaceM4/FGVC-Aircraft](https://huggingface.co/datasets/HuggingFaceM4/FGVC-Aircraft)
+- [mteb/FGVCAircraftZeroShot](https://huggingface.co/datasets/mteb/FGVCAircraftZeroShot)
 
 
 ## How to evaluate on this task
@@ -357,10 +357,8 @@ You can evaluate an embedding model on this dataset using the following code:
 import mteb
 
 task = mteb.get_task("FGVCAircraftZeroShot")
-evaluator = mteb.MTEB([task])
-
 model = mteb.get_model(YOUR_MODEL)
-evaluator.run(model)
+mteb.evaluate(model, task)
 ```
 
 <!-- Datasets want link to arxiv in readme to autolink dataset with paper -->
@@ -422,317 +420,331 @@ desc_stats = task.metadata.descriptive_stats
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-        "max_image_height": 1197,
-        "min_label_text_length": 38,
-        "average_label_text_length": 41.46,
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 }