| 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](https://github.com/Arys02/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 | |
| ```bash | |
| python -m scripts.fetch_sage_models # from the hub repository: downloads and checks both SAGE models into models/ | |
| ``` | |