Update README.md

README.md

@@ -1,39 +1,27 @@
 ---
+language:
+- en
+license: lgpl-3.0
+library_name: pytorch
 tags:
-- generated_from_keras_callback
-model-index:
-- name: distilbert-political-tweets
-  results: []
+- text-classification  # Example: audio
+- transformers  # Example: automatic-speech-recognition
+- pytorch  # Example: speech
+datasets:
+- m-newhauser/senator-tweets  # Example: common_voice. Use dataset id from https://hf.co/datasets
+metrics:
+- accuracy  # Example: wer. Use metric id from https://hf.co/metrics
+- f1
+widget:
+- text: "This pandemic has shown us clearly the vulgarity of our healthcare system. Highest costs in the world, yet not enough nurses or doctors. Many millions uninsured, while insurance company profits soar. The struggle continues. Healthcare is a human right. Medicare for all."
+  example_title: "Bernie Sanders (D)"
+- text: "Team Biden would rather fund the Ayatollah's Death to America regime than allow Americans to produce energy for our own domestic consumption."
+  example_title: "Ted Cruz (R)"
 ---
 
-<!-- This model card has been generated automatically according to the information Keras had access to. You should
-probably proofread and complete it, then remove this comment. -->
-
 # distilbert-political-tweets
 
-This model was trained from scratch on an unknown dataset.
-It achieves the following results on the evaluation set:
-
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- optimizer: None
-- training_precision: float32
+🗣 🇺🇸 Classify sentiment as Democratic or Republican.
 
 ### Training results