Update README.md

README.md

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 license: afl-3.0
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+[Needs More Information]
+
+# Dataset Card for tiny-imagenet
+
+## Dataset Description
+
+- **Homepage:** https://www.kaggle.com/c/tiny-imagenet
+- **Repository:** [Needs More Information]
+- **Paper:** http://cs231n.stanford.edu/reports/2017/pdfs/930.pdf
+- **Leaderboard:** https://paperswithcode.com/sota/image-classification-on-tiny-imagenet-1
+- **Point of Contact:** [Needs More Information]
+
+### Dataset Summary
+
+Tiny ImageNet contains 100000 images of 200 classes (500 for each class) downsized to 64×64 colored images. Each class has 500 training images, 50 validation images, and 50 test images.
+
+### Supported Tasks and Leaderboards
+
+[Needs More Information]
+
+### Languages
+
+The class labels in the dataset are in English.
+
+## Dataset Structure
+
+### Data Instances
+
+```json
+{
+  'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=64x64 at 0x1A800E8E190,
+  'label': 15
+}
+```
+
+### Data Fields
+
+- image: A PIL.Image.Image object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0].
+- label: an int classification label. -1 for test set as the labels are missing.
+
+### Data Splits
+
+|              | Train  | Valid |
+| ------------ | ------ | ----- |
+| # of samples | 100000 | 10000 |