update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9256806475349522
+      value: 0.9349593495934959
     - name: Recall
       type: recall
-      value: 0.9416167664670658
+      value: 0.9468562874251497
     - name: F1
       type: f1
-      value: 0.9335807050092764
+      value: 0.9408702119747119
     - name: Accuracy
       type: accuracy
-      value: 0.9460950764006791
+      value: 0.9490662139219015
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,11 +43,11 @@ 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-layoutlmv3 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2933
-- Precision: 0.9257
-- Recall: 0.9416
-- F1: 0.9336
-- Accuracy: 0.9461
+- Loss: 0.2730
+- Precision: 0.9350
+- Recall: 0.9469
+- F1: 0.9409
+- Accuracy: 0.9491
 
 ## Model description
 
@@ -78,16 +78,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 4.17  | 250  | 1.0415          | 0.7691    | 0.8129 | 0.7904 | 0.8132   |
-| 1.3968        | 8.33  | 500  | 0.5604          | 0.8509    | 0.8757 | 0.8632 | 0.8722   |
-| 1.3968        | 12.5  | 750  | 0.4191          | 0.8833    | 0.9064 | 0.8947 | 0.9092   |
-| 0.3531        | 16.67 | 1000 | 0.3352          | 0.9139    | 0.9296 | 0.9217 | 0.9308   |
-| 0.3531        | 20.83 | 1250 | 0.3185          | 0.9189    | 0.9326 | 0.9257 | 0.9351   |
-| 0.161         | 25.0  | 1500 | 0.3069          | 0.9177    | 0.9349 | 0.9262 | 0.9389   |
-| 0.161         | 29.17 | 1750 | 0.2989          | 0.9270    | 0.9409 | 0.9339 | 0.9448   |
-| 0.0956        | 33.33 | 2000 | 0.2897          | 0.9242    | 0.9394 | 0.9317 | 0.9440   |
-| 0.0956        | 37.5  | 2250 | 0.2893          | 0.9242    | 0.9401 | 0.9321 | 0.9452   |
-| 0.0704        | 41.67 | 2500 | 0.2933          | 0.9257    | 0.9416 | 0.9336 | 0.9461   |
+| No log        | 4.17  | 250  | 1.0147          | 0.7119    | 0.7807 | 0.7447 | 0.7963   |
+| 1.3916        | 8.33  | 500  | 0.5211          | 0.8428    | 0.8705 | 0.8564 | 0.8786   |
+| 1.3916        | 12.5  | 750  | 0.3842          | 0.8961    | 0.9169 | 0.9064 | 0.9181   |
+| 0.3265        | 16.67 | 1000 | 0.3158          | 0.9225    | 0.9349 | 0.9286 | 0.9393   |
+| 0.3265        | 20.83 | 1250 | 0.2874          | 0.9162    | 0.9334 | 0.9247 | 0.9414   |
+| 0.139         | 25.0  | 1500 | 0.2738          | 0.9255    | 0.9394 | 0.9324 | 0.9461   |
+| 0.139         | 29.17 | 1750 | 0.2774          | 0.9354    | 0.9431 | 0.9392 | 0.9491   |
+| 0.0798        | 33.33 | 2000 | 0.2695          | 0.9342    | 0.9461 | 0.9401 | 0.9508   |
+| 0.0798        | 37.5  | 2250 | 0.2759          | 0.9356    | 0.9461 | 0.9408 | 0.9495   |
+| 0.0592        | 41.67 | 2500 | 0.2730          | 0.9350    | 0.9469 | 0.9409 | 0.9491   |
 
 
 ### Framework versions