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AcademicaMed-PACT-ClinicalTrials-Pop-256
Academica/AcademicaMed-PACT-ClinicalTrials-Pop-256
AcademicaMed-PACT-ClinicalTrials-Pop-256 is a sentence similarity model from Academica. Use it when you need a score for how close two texts are. It is set up for sentence-transformers. The card lists the license as cc-by-nc-nd-4.0.
PACT is the population and condition embedding model in the AcademicaMed clinical-trial model family.
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At a glance
- Task
- Sentence Similarity
- Library
- sentence-transformers
- License
- cc-by-nc-nd-4.0
- Access
- Public
- Created
- Aug 4, 2026
- Updated
- Aug 4, 2026
- SHA
- 437175c4
Base models
Model card
From the Hugging Face model README
AcademicaMed-PACT-ClinicalTrials-Pop-256
PACT is the population and condition embedding model in the AcademicaMed clinical-trial model family.
The model represents trial text as a 256-dimensional vector. Its contrastive objective groups trials through standardized MeSH condition terms.
Model details
| Property | Value |
|---|---|
| Base model | NeuML/pubmedbert-base-embeddings |
| Output dimension | 256 |
| Training method | Triplet-loss contrastive learning |
| Training corpus | 563,845 ClinicalTrials.gov entries |
| Grouping signal | 4,960 MeSH condition terms |
| Epochs | 10 |
| Batch size | 32 |
| Learning rate | 2e-5 |
| Loss margin | 0.5 |
| Training hardware | NVIDIA DGX Spark, GB10 Blackwell |
Intended use
PACT supports similarity analysis by enrolled population and condition. It does not estimate treatment efficacy or patient-level outcomes.
Architecture
Trial text -> PubMedBERT embedding -> dense 384-to-256 projection -> L2-normalized vector
Limitations
The training signal depends on ClinicalTrials.gov records and MeSH condition assignments. Missing or inconsistent records can affect similarity results.
This repository contains the original published model card and configuration scope. The source repository did not publish executable weight files.
AcademicaMed family
- Task
- Sentence Similarity
- Library
- sentence-transformers
- License
- cc-by-nc-nd-4.0
- Languages
- en
- Created
- Aug 4, 2026
- Updated
- Aug 4, 2026