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metadata
library_name: transformers
pipeline_tag: text-classification
tags:
  - roberta
  - speech-acts
  - peer-review
  - sage
language: en

roberta-speech-act-classifier

Speech-act classifier used by SAGE (Subjectivity-Aware Generation Estimator) of generated_text_detection_hub to label each sentence of a review.

  • Architecture: RobertaForSequenceClassification (RoBERTa-base size: 12 layers, hidden size 768, 514 positions), 5 classes.
  • Labels: 0 Assertion, 1 Expressive, 2 Neither, 3 Question, 4 Suggestion.
  • Input: one sentence (the hub splits reviews with pysbd). Max length 512 tokens.

Provenance and limits

The checkpoint this model was fine-tuned from, the training data, the training procedure and the evaluation metrics are not documented: config.json has no _name_or_path and the training code is not in the repository. No licence is stated for the weights. Use it as a component of the hub, not as a validated standalone classifier.

Use

python -m scripts.fetch_sage_models   # from the hub repository: downloads and checks both SAGE models into models/