Update README.md

README.md

@@ -47,7 +47,7 @@ size_categories:
 
 # IndicVarna for Callchimp.ai (a Dynopii product)
 
-We introduce IndiVarna which was prepared by using Google Translate the [dair-ai/emotion](https://huggingface.co/datasets/dair-ai/emotion) dataset to top 10 most commonly used Indian languages.
+We introduce IndiVarna which was prepared by using Google Translate on the [dair-ai/emotion](https://huggingface.co/datasets/dair-ai/emotion) dataset to get the samples there translated to the top 10 most commonly used Indian languages.
 
 This dataset contains `10000` samples of each of the 10 languages supported.
 
@@ -58,7 +58,7 @@ The dataset has three columns - `uuid`, `text`, `label`. `uuid` here is the conc
 This enabled us to start using the dataset out of the box with Hugging Face based text classification pipelines.
 
 The languages supported by the dataset are:
-- 1. English - `en`
+  1. English - `en`
   2. Hindi - `hi`
   3. Bengali - `bn`
   4. Gujarati - `gu`
@@ -70,7 +70,7 @@ The languages supported by the dataset are:
   10. Telugu `te`
 
 The dataset can be used to perform any of the following downstream tasks -
-- 1. Text classification (sentiment analysis models, similarity models)
+  1. Text classification (sentiment analysis models, similarity models)
   2. Text Generation - Fill mask, generation, etc. (samples can be used without the sentiment labels to prepare small corpus for text-generation fine tuning for any of the languages)
   3. Translation - every sentence can be matched with corresponding sentences of the same language code and then used to train translations models between the languages.