EvalLLM-GLiNER-Biomedical
Model Description
This model is a fine-tuned version of gliner-biomed-large-v1.0 specifically designed for French biomedical Named Entity Recognition (NER). It was developed as part of the EvalLLM 2025 challenge.
The model leverages GLiNER's zero-shot capabilities while being fine-tuned on synthetic biomedical data, making it highly effective for identifying 21 types of biomedical entities in French text.
Model Details
Base Model
- Architecture: GLiNER (Generalist and Lightweight Model for Named Entity Recognition)
- Base Version: gliner-biomed-large-v1.0
- Language: French
- Domain: Biomedical and health-related text
Training Configuration
- Training Epochs: 3 (early stopping at 2.85 epochs)
- Learning Rate: 1e-5
- Weight Decay: 0.01
- Scheduler: Cosine with 10% warm-up
- Batch Size: 8
- Training Data: 1,748 synthetic documents
Entity Types (21 categories)
Entity Type | French Label | Example |
---|---|---|
ABS_DATE |
Date absolue | "15 mars 2020" |
ABS_PERIOD |
Période absolue | "janvier 2019 à mars 2020" |
BIO_TOXIN |
Toxine biologique | "toxine botulique" |
DIS_REF_TO_PATH |
Référence maladie-pathogène | "infection par E. coli" |
DOC_AUTHOR |
Auteur de document | "Dr. Martin Dubois" |
DOC_DATE |
Date de document | "publié le 12/03/2021" |
DOC_SOURCE |
Source de document | "Journal of Medicine" |
EVENT_MACRO |
Événement macro | "épidémie de COVID-19" |
EVENT_MICRO |
Événement micro | "cas de contamination" |
EXPLOSIVE |
Explosif | "TNT", "dynamite" |
FUZZY_PERIOD |
Période floue | "début d'année", "récemment" |
INF_DISEASE |
Maladie infectieuse | "grippe", "tuberculose" |
LOCATION |
Localisation | "Paris", "France" |
LOC_REF_TO_ORG |
Référence lieu-organisation | "hôpital de Lyon" |
NON_INF_DISEASE |
Maladie non infectieuse | "diabète", "cancer" |
ORGANIZATION |
Organisation | "OMS", "Institut Pasteur" |
ORG_REF_TO_LOC |
Référence organisation-lieu | "OMS Europe" |
PATHOGEN |
Pathogène | "virus Ebola", "E. coli" |
PATH_REF_TO_DIS |
Référence pathogène-maladie | "virus causant la grippe" |
RADIOISOTOPE |
Radio-isotope | "uranium 235", "césium 137" |
REL_DATE |
Date relative | "hier", "la semaine dernière" |
REL_PERIOD |
Période relative | "depuis 3 mois" |
TOXIC_AGENT |
Agent toxique | "plomb", "mercure" |
Citation
Related Resources
- GitHub Repository: EvalLLM2025
- Paper: [Link to paper when published]
- Challenge: EvalLLM 2025
License
This model is released under the Apache 2.0 License.
Acknowledgments
- GLiNER team for the base architecture
- EvalLLM 2025 organizers
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Model tree for ik-ram28/EvalLLM-GLiNER
Base model
microsoft/deberta-v3-large
Finetuned
Ihor/gliner-biomed-large-v1.0