Update README.md

README.md

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 ### Model Description
 
-MiewID-msv2 is a feature extractor pretrained re-identification task on a large, high-quality dataset of 54 wildlife species - terrestrial and aquatic - including fins, flukes, flanks, faces.
+MiewID-msv2 is a feature extractor trained for re-identification using contrastive learning on a large, high-quality dataset of 54 wildlife species - terrestrial and aquatic - including fins, flukes, flanks, faces.
 
 - **Model Type:** Wildlife re-identification feature backbone
 - **Model Stats:**
@@ -71,20 +71,9 @@ View more usage examples at https://github.com/WildMeOrg/wbia-plugin-miew-id/tre
 
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
 
-The dataset used for these experiments was a combination of data from Wildbook platforms (multiple users) and
-the Happywhale Kaggle competitions multi-species dataset. The latter is available for
-non-commercial purposes and academic research and education. A subset of data from Wildbook platforms is available at https://lila.science/datasets. There are two main distinctions
-between the Happywhale and Wildbook datasets in addition to different species coverage as used
-in our experiments.
-The Happywhale dataset did not have viewpoint labels (e.g., left, right, top, bottom), which can
-refine re-ID training approaches.
-The bounding boxes for the annotations of interest (AoI) in the Happywhale-sourced data were
-generated using a pre-trained Detic model (developed during the contest). 
-Where the datasets overlapped by species, only one dataset was used to ensure no duplication of
-individuals was present. Not every species from the Happywhale dataset was incorporated, with
-limited data excluding some underrepresented species wholesale. For selected species, no
-filtering was done on the basis of quality or distinctiveness, with real-world data valued for its
-diversity.
+The dataset used for these experiments was a combination of data from Wildbook platforms (multiple users), Happywhale Kaggle competitions multi-species dataset and multiple publicly available datasets. The latter is available for
+non-commercial purposes and academic research and education. A subset of data from Wildbook platforms is available at https://lila.science/datasets. 
+
 
 ### Example images