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
- 44
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.