distilbert-political-tweets π£ πΊπΈ
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
- Downloads last month
- 106
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.