Create README.md

README.md

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+---
+language: en
+license: cc-by-nc-4.0
+library_name: transformers
+pipeline_tag: token-classification
+tags:
+- veterinary
+- nlp
+- named-entity-recognition
+- biomedical
+- feline
+---
+
+# Feline-NER
+
+## Model Description
+**Feline-NER** is a transformer-based named entity recognition (NER) model for **feline veterinary scientific literature**.
+
+The model follows the BERT architecture and was initialized from **BioBERT v1.2**, further domain-adapted on feline-related PubMed Central articles (*Feline-BERT*), and fine-tuned for NER (*Feline-NER*).
+
+This model is intended **solely for research and educational use**.
+
+## Task
+Span-level named entity recognition using a BIO tagging scheme over five entity types:
+- DISEASE
+- SYMPTOM
+- MEDICATION
+- PROCEDURE
+- ANATOMY
+
+## Training Data
+Fine-tuned on a manually annotated dataset of **1,300 sentences** extracted from feline-related PubMed Central articles.
+Annotations were produced by a non-veterinary researcher using an iterative human-in-the-loop workflow with LLM-assisted pre-labeling.
+
+## Evaluation
+- **Macro F1:** ~0.65  
+- **Micro F1:** ~0.64  
+(Evaluated on a 150-sentence held-out test set)
+
+Performance varies by entity type; PROCEDURE and ANATOMY remain challenging due to boundary ambiguity.
+
+## Intended Use
+- Veterinary NLP research
+- Information extraction from feline scientific literature
+- Educational demonstrations
+
+## ⚠️ Limitations & Warnings
+- **NOT FOR CLINICAL USE**
+- Not validated for diagnosis or treatment
+- Annotation noise and boundary ambiguity are present
+- Single-annotator dataset
+
+## Author
+Statistical-Impossibility