updated readme

README.md

@@ -637,7 +637,7 @@ dataset.regions
 
 <img src="./assets/tiselac.png" width="900px"></img>
 
-The TiSeLaC dataset from the [Time Series Land Cover Classification Challenge](https://sites.google.com/site/dinoienco/tiselac-time-series-land-cover-classification-challenge) is a time series land cover classification dataset consisting of 23 2866x2633 medium resolution (30m) multispectral 10 band (7 reflectance + NDVI/NDWI/Brightness Index) images taken by the [USGS Landsat 8 satellite](https://www.usgs.gov/core-science-systems/nli/landsat/landsat-8). The imagery was captured over Reunion Island in 2014 and contains 9 land cover classes derived from the [Corine Land Cover (CLC) map](https://land.copernicus.eu/pan-european/corine-land-cover). Note that the dataset is formatted for pixelwise time-series classification where each time series is of the form `(t, b)` where `t=23 samples` and `b=10 bands`.
+The TiSeLaC dataset from the [Time Series Land Cover Classification Challenge](https://sites.google.com/site/dinoienco/tiselac-time-series-land-cover-classification-challenge) is a time series land cover classification dataset consisting of 23 2866x2633 medium resolution (30m) multispectral 10 band (7 reflectance + NDVI/NDWI/Brightness Index) images taken by the [USGS Landsat 8 satellite](https://www.usgs.gov/core-science-systems/nli/landsat/landsat-8). The imagery was captured over Reunion Island in 2014 and contains 9 land cover classes derived from the [Corine Land Cover (CLC) map](https://land.copernicus.eu/pan-european/corine-land-cover). Note that the dataset is formatted for pixelwise time-series classification where each time series is of the form `(t, b)` where `t=23 samples` and `b=10 bands`. This dataset is very easy with the top score currently standing at `0.9929` F1 Score.
 
 The dataset can be downloaded (.08GB) using `scripts/download_tiselac.sh` and instantiated below: