From bc247f6ece17d4bc6735739a7a8c5ce7d8ecd6a3 Mon Sep 17 00:00:00 2001 From: Gabriel Ilharco Date: Wed, 25 Oct 2023 21:49:17 +0000 Subject: [PATCH] Add retrieval and classification result tables --- docs/PRETRAINED.md | 4 +- docs/openclip_classification_results.csv | 116 +++++++++++++++++++++++ docs/openclip_retrieval_results.csv | 116 +++++++++++++++++++++++ 3 files changed, 235 insertions(+), 1 deletion(-) create mode 100644 docs/openclip_classification_results.csv create mode 100644 docs/openclip_retrieval_results.csv diff --git a/docs/PRETRAINED.md b/docs/PRETRAINED.md index 5bb72a6cb..148a83c0d 100644 --- a/docs/PRETRAINED.md +++ b/docs/PRETRAINED.md @@ -3,7 +3,9 @@ We evaluate the full collection of available models on a suite of 38 datasets in a zero-shot setting (i.e., without fine-tuning), following [Gadre et al., 2023](https://arxiv.org/abs/2304.14108). Click below to see the full results. -[Full results](docs/openclip_results.csv) +- [Full results](openclip_results.csv) +- [Retrieval results](openclip_retrieval_results.csv) +- [Classification-only results](openclip_classification_results.csv) ## Pretrained model details diff --git a/docs/openclip_classification_results.csv b/docs/openclip_classification_results.csv new file mode 100644 index 000000000..5f6f75a33 --- /dev/null +++ b/docs/openclip_classification_results.csv @@ -0,0 +1,116 @@ +name,pretrained,params (M),FLOPs (B),Average perf. on 35 datasets,ImageNet 1k,Caltech-101,CIFAR-10,CIFAR-100,CLEVR Counts,CLEVR Distance,Country211,Describable Textures,EuroSAT,FGVC Aircraft,Food-101,GTSRB,ImageNet Sketch,ImageNet v2,ImageNet-A,ImageNet-O,ImageNet-R,KITTI Vehicle Distance,MNIST,ObjectNet,Oxford Flowers-102,Oxford-IIIT Pet,Pascal VOC 2007,PatchCamelyon,Rendered SST2,RESISC45,Stanford Cars,STL-10,SUN397,SVHN,iWildCam,Camelyon17,FMoW,Dollar Street,GeoDE 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+EVA01-g-14-plus,merged2b_s11b_b114k,1366.62,581.15,0.6645,0.7933,0.9506,0.9910,0.9008,0.2302,0.2293,0.3087,0.6734,0.7280,0.3947,0.9366,0.6644,0.6814,0.7214,0.7416,0.3415,0.9246,0.1491,0.7176,0.7491,0.7959,0.9490,0.8285,0.6244,0.5854,0.7079,0.9073,0.9949,0.7426,0.5951,0.1882,0.7100,0.2283,0.6589,0.9148 +ViT-L-14-CLIPA-336,datacomp1b,414.54,387.39,0.6609,0.8026,0.9439,0.9864,0.8826,0.1566,0.2439,0.3066,0.6856,0.5811,0.4281,0.9456,0.5695,0.7087,0.7346,0.7771,0.3290,0.9329,0.1997,0.7667,0.7317,0.8100,0.9495,0.7979,0.6028,0.5316,0.6884,0.9407,0.9929,0.7560,0.6290,0.1937,0.6783,0.2500,0.6752,0.9240 +ViT-L-14-quickgelu,metaclip_fullcc,427.62,175.33,0.6607,0.7917,0.9527,0.9759,0.8410,0.3107,0.2260,0.3394,0.6862,0.5894,0.4537,0.9352,0.5623,0.6896,0.7256,0.7231,0.3010,0.9205,0.2785,0.6444,0.7457,0.8143,0.9461,0.8030,0.6197,0.6678,0.7360,0.8868,0.9933,0.7355,0.4681,0.1581,0.7551,0.2592,0.6752,0.9140 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+convnext_xxlarge,laion2b_s34b_b82k_augreg_soup,1200.58,443.03,0.6545,0.7947,0.9448,0.9822,0.8687,0.1454,0.2365,0.3170,0.7053,0.6128,0.4434,0.9321,0.5508,0.6840,0.7260,0.6719,0.4060,0.9160,0.2363,0.8277,0.7273,0.8241,0.9445,0.8090,0.5142,0.6952,0.7190,0.9409,0.9810,0.7458,0.6254,0.1730,0.6071,0.0000,0.6764,0.9215 +convnext_xxlarge,laion2b_s34b_b82k_augreg_rewind,1200.58,443.03,0.6534,0.7931,0.9452,0.9823,0.8686,0.1651,0.2534,0.3155,0.7016,0.6331,0.4398,0.9308,0.5491,0.6825,0.7228,0.6657,0.3975,0.9139,0.2419,0.7930,0.7252,0.8241,0.9438,0.8100,0.5014,0.6897,0.7168,0.9406,0.9801,0.7459,0.6137,0.1735,0.6071,0.0000,0.6799,0.9228 +ViT-L-16-SigLIP-256,webli,652.15,201.62,0.6534,0.8045,0.9593,0.9619,0.8191,0.4065,0.2150,0.2141,0.7027,0.5598,0.5259,0.9463,0.6115,0.7209,0.7376,0.6213,0.3265,0.9396,0.1983,0.8499,0.6526,0.8827,0.9604,0.7409,0.5458,0.6172,0.6817,0.9386,0.9911,0.7253,0.5211,0.1796,0.5757,0.1296,0.6904,0.9173 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R@1,Flickr image retr. R@5,Flickr image retr. R@10,Flickr text retr. R@1,Flickr text retr. R@5,Flickr text retr. R@10,MSCOCO image retr. R@1,MSCOCO image retr. R@5,MSCOCO image retr. R@10,MSCOCO text retr. R@1,MSCOCO text retr. R@5,MSCOCO text retr. R@10,WinoGAViL avg jaccard score,WinoGAViL jaccard score 10,WinoGAViL jaccard score 10-12,WinoGAViL jaccard score 12,WinoGAViL jaccard score 5,WinoGAViL jaccard score 5-6,WinoGAViL jaccard score 6 +ViT-SO400M-14-SigLIP-384,webli,877.96,723.48,0.7721,0.8296,0.9610,0.9804,0.9430,0.9970,0.9980,0.5421,0.7678,0.8424,0.7242,0.8998,0.9448,0.6181,0.5807,0.5754,0.5701,0.6427,0.6316,0.6210 +ViT-L-16-SigLIP-384,webli,652.48,422.91,0.7642,0.8142,0.9536,0.9748,0.9370,0.9920,0.9990,0.5391,0.7657,0.8399,0.7190,0.9006,0.9410,0.6070,0.5562,0.5550,0.5539,0.6422,0.6234,0.6056 +ViT-L-16-SigLIP-256,webli,652.15,201.62,0.7619,0.7904,0.9446,0.9684,0.9180,0.9900,0.9980,0.5228,0.7580,0.8334,0.7080,0.8870,0.9374,0.6142,0.5877,0.5748,0.5619,0.6450,0.6267,0.6092 +ViT-SO400M-14-SigLIP,webli,877.36,233.54,0.7567,0.7526,0.9226,0.9554,0.9100,0.9910,0.9980,0.5176,0.7527,0.8300,0.6966,0.8908,0.9348,0.6189,0.5736,0.5665,0.5594,0.6430,0.6354,0.6282 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