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Biomed-Enriched-classifier
almanach/Biomed-Enriched-classifier
Biomed-Enriched-classifier is a machine learning model from almanach. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
This is the model used to create the Biomed-Enriched dataset.
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At a glance
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Jan 7, 2025
- Updated
- Jun 26, 2025
- SHA
- 9c384e00
Base models
Model card
From the Hugging Face model README
Biomedical-Enriched Classifier
This is the model used to create the Biomed-Enriched dataset.
Model Details
- Base Model:
xlm-roberta-base - Model Type: Multi-task model combining multi-label classification and regression.
- Description: This model was fine-tuned to classify paragraphs from biomedical texts for their domain and document type, and predict an educational quality score via regression.
Training
The model was trained on a set of 400,000 paragraphs from PubMed Central, which were annotated by the Llama 3.1 70B Instruct model.
Purpose
This classifier was created to scale the initial high-quality annotations to the entire PubMed Open Access dataset. This distillation process enabled the creation of the large-scale Biomed-Enriched dataset while maintaining annotation consistency.
Model Outputs
The model predicts the following outputs:
Domain (Classification)
ClinicalBiomedicalOther
Document Type (Classification)
Clinical CaseStudyReviewOther
Educational Quality (Regression)
- A regression score from
1(low quality) to5(high quality).
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Jan 7, 2025
- Updated
- Jun 26, 2025