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roberta-babe-baseline
vulonviing/roberta-babe-baseline
roberta-babe-baseline is a text classification model from vulonviing. Use it when you need a label for a piece of text. It is set up for transformers.
Best-fold checkpoint from a 5-fold RoBERTa-base reproduction of BABE sentence-level media bias classification.
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Apr 8, 2026
- Updated
- Apr 8, 2026
- SHA
- 9ae49768
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Base models
Datasets
Model card
From the Hugging Face model README
roberta-babe-baseline
Best-fold checkpoint from a 5-fold RoBERTa-base reproduction of BABE sentence-level media bias classification.
- Training code: https://github.com/vulonviing/babe-roberta-baseline
- Source dataset: https://huggingface.co/datasets/mediabiasgroup/BABE
- Released checkpoint:
models/fold_0/checkpoint-532 - Selected checkpoint:
fold_0with macro-F10.876 - Summary statement: trained on 80% of BABE, 5-fold CV mean:
0.857 +- 0.012
Model details
| Item | Value |
|---|---|
| Base model | roberta-base |
| Task | Sentence-level media bias classification |
| Labels | non-biased, biased |
| Max sequence length | 128 |
| Epochs | 4 |
| Learning rate | 2e-05 |
| Batch size | 16 train / 32 eval |
| Weight decay | 0.01 |
| Warmup ratio | 0.1 |
| Random seed | 42 |
Cross-validation summary
| Metric | Mean +- Std |
|---|---|
| Macro-F1 | 0.857 +- 0.012 |
| Accuracy | 0.858 +- 0.012 |
| Precision (macro) | 0.856 +- 0.011 |
| Recall (macro) | 0.859 +- 0.012 |
| Biased F1 | 0.869 +- 0.011 |
Per-fold macro-F1 values in the repo: 0.876, 0.854, 0.845, 0.852, 0.856.
Held-out quick-run reference
| Metric | Score |
|---|---|
| Macro-F1 | 0.870 |
| Accuracy | 0.872 |
| Precision (macro) | 0.870 |
| Recall (macro) | 0.872 |
| Biased F1 | 0.884 |
Confusion matrix from the held-out quick run (n=468):
| Pred non-biased | Pred biased | |
|---|---|---|
| True non-biased (207) | 180 | 27 |
| True biased (261) | 33 | 228 |
Usage
from transformers import AutoModelForSequenceClassification, AutoTokenizer
repo_id = 'vulonviing/roberta-babe-baseline'
tokenizer = AutoTokenizer.from_pretrained(repo_id)
model = AutoModelForSequenceClassification.from_pretrained(repo_id)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Languages
- en
- Created
- Apr 8, 2026
- Updated
- Apr 8, 2026