Update README.md

README.md

@@ -28,9 +28,50 @@ task_categories:
 - text-classification
 language:
 - en
+tags:
+- coffeshop
+- customer
+size_categories:
+- 1K<n<10K
 ---
 
 
+**Dataset Card: Bike Shop Chat-bot Intents**
+
+**Dataset Name:** Bike Shop Chat-bot Intents
+
+**Description:** This dataset contains phrases labeled by intents, used to train and test a chat-bot for a bike shop. The intents represent the underlying goals or actions that users want to perform when interacting with the chat-bot.
+
+**Files:**
+
+* **intents_train.csv**: The training dataset, containing labeled phrases and their corresponding intents.
+* **intents_test.csv**: The testing dataset, containing phrases to be classified into intents.
+
+**Data Type:** Text data (phrases) with categorical labels (intents)
+
+**Size:**
+
+* **intents_train.csv**: [Insert number of rows/samples] phrases
+* **intents_test.csv**: [Insert number of rows/samples] phrases
+
+**Variables:**
+
+* **Phrase**: The text input from users, representing their queries or requests.
+* **Intent**: The categorical label assigned to each phrase, indicating the underlying goal or action.
+
+**Data Collection:** The dataset was likely created by collecting phrases from various sources, such as customer interactions, online reviews, or forums, and then labeling them with corresponding intents.
+
+**Data Processing:** The phrases were likely preprocessed by tokenizing, removing stop words, and stemming/lemmatizing to prepare them for model training.
+
+**Task:** The task is to develop a model that can classify new, unseen phrases into their corresponding intents, based on the patterns learned from the training data.
+
+**Potential Applications:**
+
+* Improving the chat-bot's ability to understand user requests and respond accurately.
+* Enhancing the overall customer experience by providing more effective support and guidance.
+* Identifying trends and insights from user interactions to inform business decisions.
+
+
 ---
 license: mit
 ---