Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+task_categories:
+- text-classification
+tags:
+- sentiment analysis
+- amazon
+- reviews
+- fine_grained
+- text data
+- nlp
+pretty_name: Amazon Reviewsfor Binary Sentiment Analysis
+---
+# Dataset Card for Dataset Name
+
+The Amazon reviews full score dataset is constructed by randomly taking 600,000 training samples and 130,000 testing samples for each review score from 1 to 5. In total there are 3,000,000 trainig samples and 650,000 testing samples.
+
+## Dataset Details
+
+### Dataset Description
+
+The files train.csv and test.csv contain all the training samples as comma-sparated values. There are 3 columns in them, corresponding to class index (1 to 5), review title and review text. The review title and text are escaped using double quotes ("), and any internal double quote is escaped by 2 double quotes (""). New lines are escaped by a backslash followed with an "n" character, that is "\n".
+- **License:** Apache 2
+
+### Dataset Sources [optional]
+
+<!-- Provide the basic links for the dataset. -->
+
+- **Link on Kaggle:** https://www.kaggle.com/datasets/yacharki/amazon-reviews-for-sentianalysis-finegrained-csv
+- **DOI:** @misc{xiang_zhang_acharki_yassir_2022,
+	title={🛒 Amazon Reviews for SA fine-grained 5 classes},
+	url={https://www.kaggle.com/dsv/3499094},
+	DOI={10.34740/KAGGLE/DSV/3499094},
+	publisher={Kaggle},
+	author={Xiang Zhang and Acharki Yassir},
+	year={2022}
+}
+
+## Uses
+
+NLP
+
+### Direct Use
+
+Fine grained sentiment analysis
+
+
+## Dataset Structure
+
+The Dataset Contains 
+
+readme.txt
+
+test.csv
+
+train.csv
+
+
+## Dataset Card Contact
+
+For more info visit : 
+
+https://www.kaggle.com/datasets/yacharki/amazon-reviews-for-sentianalysis-finegrained-csv