Upload artifacts (small scale)
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small_scale/results.jsonl
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{"key": "vtab/caltech101", "dataset": "Caltech-101", "metrics": {"acc1": 0.39178307313064914, "acc5": 0.6898931799506984, "mean_per_class_recall": 0.3573535575129946, "main_metric": 0.3573535575129946}}
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{"key": "cifar10", "dataset": "CIFAR-10", "metrics": {"acc1": 0.5789, "acc5": 0.9738, "mean_per_class_recall": 0.5789, "main_metric": 0.5789}}
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{"key": "vtab/cifar100", "dataset": "CIFAR-100", "metrics": {"acc1": 0.2905, "acc5": 0.6048, "mean_per_class_recall": 0.2905, "main_metric": 0.2905}}
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{"key": "vtab/clevr_count_all", "dataset": "CLEVR Counts", "metrics": {"acc1": 0.14933333333333335, "acc5": 0.6446, "mean_per_class_recall": 0.14846225210925348, "main_metric": 0.14933333333333335}}
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{"key": "vtab/clevr_closest_object_distance", "dataset": "CLEVR Distance", "metrics": {"acc1": 0.203, "acc5": 0.9186666666666666, "mean_per_class_recall": 0.15483015211598952, "main_metric": 0.203}}
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{"key": "country211", "dataset": "Country211", "metrics": {"acc1": 0.013696682464454976, "acc5": 0.043886255924170614, "mean_per_class_recall": 0.013696682464454976, "main_metric": 0.013696682464454976}}
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{"key": "vtab/dtd", "dataset": "Describable Textures", "metrics": {"acc1": 0.12180851063829787, "acc5": 0.2898936170212766, "mean_per_class_recall": 0.12180851063829787, "main_metric": 0.12180851063829787}}
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{"key": "vtab/eurosat", "dataset": "EuroSAT", "metrics": {"acc1": 0.29444444444444445, "acc5": 0.7644444444444445, "mean_per_class_recall": 0.2946656919107774, "main_metric": 0.29444444444444445}}
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{"key": "fgvc_aircraft", "dataset": "FGVC Aircraft", "metrics": {"acc1": 0.010801080108010801, "acc5": 0.0501050105010501, "mean_per_class_recall": 0.010659536541889482, "main_metric": 0.010659536541889482}}
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{"key": "food101", "dataset": "Food-101", "metrics": {"acc1": 0.10847524752475247, "acc5": 0.28855445544554453, "mean_per_class_recall": 0.10847524752475245, "main_metric": 0.10847524752475247}}
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{"key": "gtsrb", "dataset": "GTSRB", "metrics": {"acc1": 0.05985748218527316, "acc5": 0.23689627870150434, "mean_per_class_recall": 0.08254117998430435, "main_metric": 0.05985748218527316}}
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{"key": "imagenet_sketch", "dataset": "ImageNet Sketch", "metrics": {"acc1": 0.03810253689402425, "acc5": 0.10137750790937138, "mean_per_class_recall": 0.03808588235294118, "main_metric": 0.03810253689402425}}
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{"key": "imagenetv2", "dataset": "ImageNet v2", "metrics": {"acc1": 0.0656, "acc5": 0.1742, "mean_per_class_recall": 0.06559999999999999, "main_metric": 0.0656}}
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{"key": "imagenet-a", "dataset": "ImageNet-A", "metrics": {"acc1": 0.0196, "acc5": 0.08573333333333333, "mean_per_class_recall": 0.025413748211319614, "main_metric": 0.0196}}
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{"key": "imagenet-o", "dataset": "ImageNet-O", "metrics": {"acc1": 0.182, "acc5": 0.4225, "mean_per_class_recall": 0.18094051352843923, "main_metric": 0.182}}
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{"key": "imagenet-r", "dataset": "ImageNet-R", "metrics": {"acc1": 0.1151, "acc5": 0.2720666666666667, "mean_per_class_recall": 0.10459894836517161, "main_metric": 0.1151}}
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{"key": "vtab/kitti_closest_vehicle_distance", "dataset": "KITTI Vehicle Distance", "metrics": {"acc1": 0.2770745428973277, "acc5": null, "mean_per_class_recall": 0.19617354219959826, "main_metric": 0.2770745428973277}}
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{"key": "mnist", "dataset": "MNIST", "metrics": {"acc1": 0.1533, "acc5": 0.6329, "mean_per_class_recall": 0.1401536846821356, "main_metric": 0.1533}}
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{"key": "objectnet", "dataset": "ObjectNet", "metrics": {"acc1": 0.07575104985463552, "acc5": 0.21024012059868633, "mean_per_class_recall": 0.07514246578043296, "main_metric": 0.07575104985463552}}
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{"key": "vtab/flowers", "dataset": "Oxford Flowers-102", "metrics": {"acc1": 0.08928281021304277, "acc5": 0.26524638152545127, "mean_per_class_recall": 0.08789523635259217, "main_metric": 0.08789523635259217}}
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{"key": "vtab/pets", "dataset": "Oxford-IIIT Pet", "metrics": {"acc1": 0.09484873262469337, "acc5": 0.30471518124829655, "mean_per_class_recall": 0.09494239387497813, "main_metric": 0.09494239387497813}}
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{"key": "voc2007", "dataset": "Pascal VOC 2007", "metrics": {"acc1": 0.31316773504273504, "acc5": 0.6167200854700855, "mean_per_class_recall": 0.42820729914310407, "main_metric": 0.31316773504273504}}
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{"key": "vtab/pcam", "dataset": "PatchCamelyon", "metrics": {"acc1": 0.5045166015625, "acc5": null, "mean_per_class_recall": 0.5047282045024709, "main_metric": 0.5045166015625}}
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{"key": "renderedsst2", "dataset": "Rendered SST2", "metrics": {"acc1": 0.500823723228995, "acc5": null, "mean_per_class_recall": 0.5, "main_metric": 0.500823723228995}}
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{"key": "vtab/resisc45", "dataset": "RESISC45", "metrics": {"acc1": 0.1226984126984127, "acc5": 0.39571428571428574, "mean_per_class_recall": 0.12415206577608122, "main_metric": 0.1226984126984127}}
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{"key": "cars", "dataset": "Stanford Cars", "metrics": {"acc1": 0.024126352443725903, "acc5": 0.10707623429921652, "mean_per_class_recall": 0.02449931508465049, "main_metric": 0.024126352443725903}}
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{"key": "stl10", "dataset": "STL-10", "metrics": {"acc1": 0.629375, "acc5": 0.974625, "mean_per_class_recall": 0.6293749999999999, "main_metric": 0.629375}}
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{"key": "sun397", "dataset": "SUN397", "metrics": {"acc1": 0.18546444268716553, "acc5": 0.4209316438935579, "mean_per_class_recall": 0.15099406078322206, "main_metric": 0.18546444268716553}}
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{"key": "vtab/svhn", "dataset": "SVHN", "metrics": {"acc1": 0.08209127228027044, "acc5": 0.5176321450522434, "mean_per_class_recall": 0.11271610243558924, "main_metric": 0.08209127228027044}}
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{"key": "retrieval/flickr_1k_test_image_text_retrieval", "dataset": "Flickr", "metrics": {"image_retrieval_recall@1": 0.10100000351667404, "text_retrieval_recall@1": 0.1509999930858612, "image_retrieval_recall@5": 0.26420000195503235, "text_retrieval_recall@5": 0.35499998927116394, "image_retrieval_recall@10": 0.3646000027656555, "text_retrieval_recall@10": 0.47099998593330383, "mean_recall@1": 0.12599999830126762, "main_metric": 0.12599999830126762}}
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{"key": "retrieval/mscoco_2014_5k_test_image_text_retrieval", "dataset": "MSCOCO", "metrics": {"image_retrieval_recall@1": 0.06501399725675583, "text_retrieval_recall@1": 0.09960000216960907, "image_retrieval_recall@5": 0.17461015284061432, "text_retrieval_recall@5": 0.24480000138282776, "image_retrieval_recall@10": 0.2522191107273102, "text_retrieval_recall@10": 0.3425999879837036, "mean_recall@1": 0.08230699971318245, "main_metric": 0.08230699971318245}}
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{"key": "misc/winogavil", "dataset": "WinoGAViL", "metrics": {"avg_jaccard_score": 0.40335591997113185, "jaccard_score_5": 0.4498232323232323, "jaccard_score_6": 0.42147828173746105, "jaccard_score_10": 0.3219092331768388, "jaccard_score_12": 0.28229862038273257, "jaccard_score_5-6": 0.4352897748246586, "jaccard_score_10-12": 0.3020575443292071, "main_metric": 0.3020575443292071}}
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{"key": "wilds/iwildcam", "dataset": "iWildCam", "metrics": {"acc1": 0.12967680119651329, "acc5": 0.21635390619522796, "mean_per_class_recall": 0.013105174040215044, "acc_avg": 0.12967680394649506, "recall-macro_all": 0.013105174040215044, "F1-macro_all": 0.006112641604645059, "main_metric": 0.006112641604645059}}
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small_scale/samples/sample_ids.npy
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