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README.md

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 # Model Card for PathBLIP-2
 
-A vision-language model built upon the BLIP-2 framework in combination with BioGPT and HIPT for pathology report generation and cross-modal retrieval of melanocytic lesions.
+A vision-language model built upon the BLIP-2 framework using BioGPT and HIPT for pathology report generation and cross-modal retrieval of melanocytic lesions.
 
 ## Model Details
 
-This repository contains multiple checkpoints for the models which were used for the experiments in the paper.
-The models were trained on a dataset of 19,636 melanocytic lesion cases, consisting of one or more whole slide images (WSIs) and a pathology report, using different training configurations. 
+This repository contains multiple checkpoints for the model which was used for the experiments in the paper.
+The model was trained and evaluated on a dataset of 19,636 melanocytic lesion cases, consisting of one or more whole slide images (WSIs) and a pathology report, using different training configurations. 
 The supporting code is available from the corresponding GitHub repository.
-We refer to the paper for more information regarding the dataset, finetuning, evaluation, and limitations.
+We refer to the paper for more information regarding the dataset, training, evaluation, and limitations.
 
 - **Paper: *["On the Importance of Text Preprocessing for Multimodal Representation Learning and Pathology Report Generation"](https://arxiv.org/abs/2502.19285)***
 - **Repository:** [GitHub](https://github.com/RTLucassen/report_preprocessing)