Update README.md

README.md

@@ -2,18 +2,35 @@
 license: mit
 base_model: roberta-large-mnli
 tags:
-- generated_from_trainer
+- book
+- genre
+- book title
 metrics:
 - f1
-model-index:
-- name: roberta-large-mnli-goodreads-bookgenres-Book_cls-5e
-  results: []
+widget:
+- text: The Quantum Chip
+  example_title: Science Fiction & Fantasy
+- text: One Dollar's Journey
+  example_title: Business & Finance
+- text: Timmy The Talking Tree
+  example_title: idk fiction
+- text: The Cursed Canvas
+  example_title: Arts & Design
+- text: Hoops and Hegel
+  example_title: Philosophy & Religion
+- text: Overview of Streams in North Dakota
+  example_title: Nature
+- text: Advanced Topology
+  example_title: Non-fiction/Math
+- text: Cooking Up Love
+  example_title: Food & Cooking
+- text: Dr. Doolittle's Extraplanatary Commute
+  example_title: Science & Technology
+pipeline_tag: text-classification
+---
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-# roberta-large-mnli-goodreads-bookgenres-Book_cls-5e
+# roberta-large-mnli for title-genre classification
 
 This model is a fine-tuned version of [roberta-large-mnli](https://huggingface.co/roberta-large-mnli) on an unknown dataset.
 It achieves the following results on the evaluation set:
@@ -22,15 +39,10 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
-
-More information needed
+This classifies one or more **genre** labels in a **multi-label** setting for a given book **title**.
 
-## Training and evaluation data
+The 'standard' way of interpreting the predictions is that the predicted labels for a given example are **only the ones with a greater than 50% probability.**
 
-More information needed
 
 ## Training procedure