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README.md

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 ## Model Description:
 
-This model is a fine-tuned version of Google's MedGemma, specialized for abstractive summarization of clinical case reports in Portuguese. It was developed as part of our submission to the MultiClinSum 2025 shared task (Portuguese track), organized under the BioASQ Lab at CLEF.
+This model is a fine-tuned version of Google's MedGemma, specialized for abstractive summarization of clinical case reports in Portuguese. It was developed as part of our submission to the [MultiClinSum 2025 shared task](https://temu.bsc.es/multiclinsum) (Portuguese track), organized under the [BioASQ Lab at CLEF](https://www.bioasq.org/).
 
 Despite being compact (4B parameters), the model achieved strong semantic alignment with expert-generated summaries, as measured by BERTScore, and competitive results overall when compared to larger instruction-tuned models in zero-shot settings.
 
 ## Training Details:
 
-Base model: https://huggingface.co/unsloth/medgemma-4b-it
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-Dataset: Subset of the MultiClinSum Portuguese gold dataset (542 examples for training, 50 for validation)
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-Framework: Transformers + PEFT + LoRA (via Unsloth)
+- Base model: https://huggingface.co/unsloth/medgemma-4b-it
+- Dataset: Subset of the MultiClinSum Portuguese gold dataset (542 examples for training, 50 for validation)
+- Framework: Transformers + PEFT + LoRA (via Unsloth)
 
 ## Use Cases:
 
 - Clinical case summarization (Portuguese)
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 - Biomedical NLP research
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 - Low-resource summarization studies
 
 ## Limitations:
 
 - Performance may vary outside of the clinical case report domain
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 - Sensitive to prompt design
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 - Trained on a small subset.
 
 ## License