--- language: - en license: lgpl-3.0 library_name: pytorch tags: - 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)" --- # distilbert-political-tweets πŸ—£ πŸ‡ΊπŸ‡Έ Classify sentiment as Democratic or Republican. ### Training results ### Framework versions - Transformers 4.16.2 - TensorFlow 2.8.0 - Datasets 1.18.3 - Tokenizers 0.11.6