update model card README.md

README.md

@@ -21,16 +21,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9190581309786607
+      value: 0.9619686800894854
     - name: Recall
       type: recall
-      value: 0.9348802395209581
+      value: 0.9655688622754491
     - name: F1
       type: f1
-      value: 0.9269016697588126
+      value: 0.9637654090399701
     - name: Accuracy
       type: accuracy
-      value: 0.9384550084889643
+      value: 0.9681663837011885
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,11 +40,11 @@ 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 cord dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3056
-- Precision: 0.9191
-- Recall: 0.9349
-- F1: 0.9269
-- Accuracy: 0.9385
+- Loss: 0.1845
+- Precision: 0.9620
+- Recall: 0.9656
+- F1: 0.9638
+- Accuracy: 0.9682
 
 ## Model description
 
@@ -63,7 +63,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
+- learning_rate: 5e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
@@ -75,16 +75,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 2.0   | 100  | 1.6054          | 0.52      | 0.6130 | 0.5627 | 0.6367   |
-| No log        | 4.0   | 200  | 0.9172          | 0.7923    | 0.8278 | 0.8097 | 0.8315   |
-| No log        | 6.0   | 300  | 0.6382          | 0.8367    | 0.8630 | 0.8497 | 0.8667   |
-| No log        | 8.0   | 400  | 0.4974          | 0.8648    | 0.8907 | 0.8776 | 0.8960   |
-| 1.1589        | 10.0  | 500  | 0.4124          | 0.8769    | 0.9064 | 0.8914 | 0.9164   |
-| 1.1589        | 12.0  | 600  | 0.3767          | 0.8961    | 0.9169 | 0.9064 | 0.9236   |
-| 1.1589        | 14.0  | 700  | 0.3388          | 0.9120    | 0.9304 | 0.9211 | 0.9338   |
-| 1.1589        | 16.0  | 800  | 0.3138          | 0.9198    | 0.9356 | 0.9276 | 0.9393   |
-| 1.1589        | 18.0  | 900  | 0.3073          | 0.9176    | 0.9334 | 0.9254 | 0.9376   |
-| 0.2992        | 20.0  | 1000 | 0.3056          | 0.9191    | 0.9349 | 0.9269 | 0.9385   |
+| No log        | 2.0   | 100  | 0.5257          | 0.8223    | 0.8555 | 0.8386 | 0.8710   |
+| No log        | 4.0   | 200  | 0.3200          | 0.9118    | 0.9281 | 0.9199 | 0.9317   |
+| No log        | 6.0   | 300  | 0.2449          | 0.9298    | 0.9424 | 0.9361 | 0.9465   |
+| No log        | 8.0   | 400  | 0.1923          | 0.9472    | 0.9536 | 0.9504 | 0.9597   |
+| 0.4328        | 10.0  | 500  | 0.1857          | 0.9591    | 0.9656 | 0.9623 | 0.9682   |
+| 0.4328        | 12.0  | 600  | 0.2073          | 0.9597    | 0.9618 | 0.9607 | 0.9656   |
+| 0.4328        | 14.0  | 700  | 0.1804          | 0.9634    | 0.9663 | 0.9649 | 0.9703   |
+| 0.4328        | 16.0  | 800  | 0.1882          | 0.9634    | 0.9648 | 0.9641 | 0.9665   |
+| 0.4328        | 18.0  | 900  | 0.1800          | 0.9619    | 0.9648 | 0.9634 | 0.9677   |
+| 0.0318        | 20.0  | 1000 | 0.1845          | 0.9620    | 0.9656 | 0.9638 | 0.9682   |
 
 
 ### Framework versions