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distilbert-political-tweets
m-newhauser/distilbert-political-tweets
distilbert-political-tweets is a text classification model from m-newhauser. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as lgpl-3.0.
This model is a fine-tuned version of distilbert-base-uncased on the m-newhauser/senator-tweets dataset, which contains all tweets made by United States senators during the first year of the Biden Administration.
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- lgpl-3.0
- Model type
- distilbert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Jul 7, 2022
- SHA
- b7c4530e
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Datasets
Model card
From the Hugging Face model README
distilbert-political-tweets 🗣 🇺🇸
This model is a fine-tuned version of distilbert-base-uncased on the m-newhauser/senator-tweets dataset, which contains all tweets made by United States senators during the first year of the Biden Administration. It achieves the following results on the evaluation set:
- Accuracy: 0.9076
- F1: 0.9117
Model description
The goal of this model is to classify short pieces of text as having either Democratic or Republican sentiment. The model was fine-tuned on 99,693 tweets (51.6% Democrat, 48.4% Republican) made by US senators in 2021.
Model accuracy may not hold up on pieces of text longer than a tweet.
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: Adam
- training_precision: float32
- learning_rate = 5e-5
- num_epochs = 5
Framework versions
- Transformers 4.16.2
- TensorFlow 2.8.0
- Datasets 1.18.3
- Tokenizers 0.11.6
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- lgpl-3.0
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Jul 7, 2022