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@@ -67,7 +67,7 @@ For quick start please have a look this [demo](https://github.com/ahmedssabir/Te
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  1. [Downlod Data with cosine score](https://www.dropbox.com/s/55sit8ow9tems4u/visual_caption_cosine_score.zip?dl=0)-> soft cosine lable with **th** 0.2, 0.3, 0.4 and 0.5 and hardlabel [0,1]
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  2. [Dowload Overlaping visual with caption](https://www.dropbox.com/s/br8nhnlf4k2czo8/COCO_overlaping_dataset.txt?dl=0)-> Overlap visual context and the human annotated caption
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  3. [Download Dataset (tsv file)](https://www.dropbox.com/s/dh38xibtjpohbeg/train_all.zip?dl=0) 0.0-> raw data with hard lable without cosine similairty and with **th**reshold cosine sim degree of the relation beteween the visual and caption = 0.2, 0.3, 0.4
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- 4. [Download Dataset GenderBias](https://www.dropbox.com/s/1wki0b0d21078mj/gender%20natural.zip?dl=0)-> man/woman replaced with person class label
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  1. [Downlod Data with cosine score](https://www.dropbox.com/s/55sit8ow9tems4u/visual_caption_cosine_score.zip?dl=0)-> soft cosine lable with **th** 0.2, 0.3, 0.4 and 0.5 and hardlabel [0,1]
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  2. [Dowload Overlaping visual with caption](https://www.dropbox.com/s/br8nhnlf4k2czo8/COCO_overlaping_dataset.txt?dl=0)-> Overlap visual context and the human annotated caption
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  3. [Download Dataset (tsv file)](https://www.dropbox.com/s/dh38xibtjpohbeg/train_all.zip?dl=0) 0.0-> raw data with hard lable without cosine similairty and with **th**reshold cosine sim degree of the relation beteween the visual and caption = 0.2, 0.3, 0.4
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+ <!-- 4. [Download Dataset GenderBias](https://www.dropbox.com/s/1wki0b0d21078mj/gender%20natural.zip?dl=0)-> man/woman replaced with person class label -->
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