Model save

README.md

@@ -26,16 +26,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.3757836288733656
+      value: 0.37793301092602544
     - name: Recall
       type: recall
-      value: 0.3757836288733656
+      value: 0.37793301092602544
     - name: F1
       type: f1
-      value: 0.3757836288733656
+      value: 0.37793301092602544
     - name: Accuracy
       type: accuracy
-      value: 0.3757836288733656
+      value: 0.37793301092602544
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -45,11 +45,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the doc_lay_net-small dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.1804
-- Precision: 0.3758
-- Recall: 0.3758
-- F1: 0.3758
-- Accuracy: 0.3758
+- Loss: 2.0791
+- Precision: 0.3779
+- Recall: 0.3779
+- F1: 0.3779
+- Accuracy: 0.3779
 
 ## Model description