Update README.md

README.md

@@ -15,9 +15,11 @@ model-index:
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-# FakevsRealNews
+# Fatima Fellowship Coding challenge
+The challenge involved building a fake news classifier using the huggingface library.
+
+This final model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an fake-and-real-news dataset. The link to the dataset is https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset.
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.0000
 - Accuracy: 1.0
@@ -27,17 +29,15 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
+Finetuned Distilbert
+ 
 ## Training and evaluation data
 
-More information needed
+The training data was split into train-dev-test in the ratio 80-10-10.
 
 ## Training procedure
+The title and text of each news story was concatenated to form each datapoint. Then a model was finetuned to perform single label classification on each datapoint. The final prediction is the class with the highest probability.
+
 
 ### Training hyperparameters