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README.md

@@ -20,10 +20,10 @@ This model is fine-tuned from [microsoft/Florence-2-base-ft](https://huggingface
 - Fine-tuned for answering questions about images, specifically focused on logo recognition and company information.
 - The model uses the `<DocVQA>` prompt to indicate the task type.
 - Number of unique images: 28
-- Number of epochs: 15
-- Learning rate: 5e-06
+- Number of epochs: 7
+- Learning rate: 1e-06
 - Optimizer: AdamW
-- Early stopping: Patience of 3 epochs, delta of 0.01
+- Early stopping: Patience of 2 epochs, delta of 0.0001
 
 Dataset statistics: Total number of questions for fine-tuning: 560.
 logo_recognition: 49 (8.75%) brand_identification: 48 (8.57%) visual_elements: 65 (11.61%) text_in_logo: 57 (10.18%) industry_classification: 49 (8.75%) product_service: 55 (9.82%) company_details: 89 (15.89%) negative_sample: 148 (26.43%)
@@ -38,7 +38,7 @@ logo_recognition: 49 (8.75%) brand_identification: 48 (8.57%) visual_elements: 6
 - Images were resized and normalized according to Florence-2's preprocessing standards.
 - The `<DocVQA>` prompt was used during fine-tuning to indicate the task type.
 - Questions and answers were provided for each image in the training set.
-- Batch size: 2
+- Batch size: 4
 - Evaluation metric: Cross-entropy loss on a held-out validation set
 
 For more information, please contact the model creators.