Update README.md

README.md

@@ -44,7 +44,7 @@ task_ids: []
   - [Action List](#action-list)
   - [Skeleton Features](#skeleton-features)
   - [Machine Learning Techniques](#machine-learning-techniques)
-- [Caveat](#caveat)
+- [Note](#note)
 - [Acknowledgements](#acknowledgements)
   - [Dataset Curators](#dataset-curation)
   - [Funding and Support](#funding-and-support)
@@ -140,8 +140,8 @@ Human action recognition often utilizes deep learning techniques to analyze and
 * Graph Neural Networks (GCN) : A convolutional model performed over a defined / specialized graph network as opposed to an array of pixels. A specific example of this is the Spatial-Temporal GCN (STGCN), which is popularly used among skeleton-based human action recognition.
 * Autoencoding : An unsupervised learning technique that can be used to learn sets of patterns and features shared by data. This can be particularly powerful for clustering data and quantifying differences between particular actions. This is also powerful in reducing data dimensionality - being able to represent the data using a smaller set of features than originally.
 
-## Caveat
-Some users have experienced "Job manager crashed while running this job." owing to the size of the dataset. To solve this problem, it is recommended to download the dataset in batch.
+## Note
+Some users across the Hugging Face platform have experienced the following error: “Job manager crashed while running this job.” owing to the large size of the dataset. To overcome this problem, it is recommended to download the dataset in batches.
 
 ## Acknowledgements