Update README.md

README.md

@@ -1,3 +1,13 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+---
+# Sentiment Analysis Model: Fine-Tuned DistilBERT
+
+## Overview
+This repository contains a fine-tuned version of the `distilbert-base-uncased` model, designed for sentiment analysis of tweets. The model is trained to classify the sentiment of a sentence into two categories: positive (label 0) and negative (label 1).
+
+## Model Description
+The fine-tuned model utilizes the `distilbert-base-uncased` architecture, trained on a dataset of GPT-3.5-generated tweets. It is designed to input a sentence and output a binary sentiment label, `0` for positive and `1` for negative.
+
+## Training Data
+The model was trained on a dataset consisting of tweets generated and labeled with sentiments by GPT-3.5. Each tweet in the training set was manually labeled as either positive or negative to provide ground truth for training.