Updated README.md

README.md

@@ -7,7 +7,7 @@ tags:
 model-index:
 - name: binarization-segformer-b3
   results: []
-pipeline_tag: image-to-image
+pipeline_tag: image-segmentation
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
 # binarization-segformer-b3
 
 This model is a fine-tuned version of [nvidia/segformer-b3-finetuned-cityscapes-1024-1024](https://huggingface.co/nvidia/segformer-b3-finetuned-cityscapes-1024-1024) on the same ensemble of datasets as the [SauvolaNet work](https://arxiv.org/pdf/2105.05521.pdf). The ensemble is publicly available in the official [SauvolaNet repository](https://github.com/Leedeng/SauvolaNet#datasets).
+
 It achieves the following results on the evaluation set on DIBCO metrics:
 - loss: 0.1017
 - F-measure: 0.9776
@@ -27,7 +28,7 @@ For more information on DIBCO metrics, see the [paper](https://ieeexplore.ieee.o
 
 ## Model description
 
-This model is part of on-going research on pure semantic segmentation models for document image binarization.
+This model is part of on-going research on pure semantic segmentation models adapted for document image binarization.
 
 ## Intended uses & limitations