update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 1.0
+      value: 0.0
     - name: Recall
       type: recall
-      value: 1.0
+      value: 0.0
     - name: F1
       type: f1
-      value: 1.0
+      value: 0.0
     - name: Accuracy
       type: accuracy
-      value: 1.0
+      value: 0.8750789972614282
 ---
 
 <!-- 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 generated dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0013
-- Precision: 1.0
-- Recall: 1.0
-- F1: 1.0
-- Accuracy: 1.0
+- Loss: 0.9748
+- Precision: 0.0
+- Recall: 0.0
+- F1: 0.0
+- Accuracy: 0.8751
 
 ## Model description
 
@@ -72,32 +72,10 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- training_steps: 2000
+- training_steps: 20
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 2.0   | 100  | 0.0873          | 0.958     | 0.9716 | 0.9648 | 0.9956   |
-| No log        | 4.0   | 200  | 0.0240          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
-| No log        | 6.0   | 300  | 0.0181          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
-| No log        | 8.0   | 400  | 0.0140          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
-| 0.1307        | 10.0  | 500  | 0.0106          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
-| 0.1307        | 12.0  | 600  | 0.0120          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
-| 0.1307        | 14.0  | 700  | 0.0080          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
-| 0.1307        | 16.0  | 800  | 0.0108          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
-| 0.1307        | 18.0  | 900  | 0.0088          | 0.972     | 0.9858 | 0.9789 | 0.9971   |
-| 0.0107        | 20.0  | 1000 | 0.0059          | 0.9919    | 0.9959 | 0.9939 | 0.9992   |
-| 0.0107        | 22.0  | 1100 | 0.0040          | 0.9960    | 0.9980 | 0.9970 | 0.9996   |
-| 0.0107        | 24.0  | 1200 | 0.0021          | 0.9980    | 0.9980 | 0.9980 | 0.9998   |
-| 0.0107        | 26.0  | 1300 | 0.0048          | 0.9919    | 0.9959 | 0.9939 | 0.9992   |
-| 0.0107        | 28.0  | 1400 | 0.0033          | 0.9960    | 0.9980 | 0.9970 | 0.9996   |
-| 0.0031        | 30.0  | 1500 | 0.0021          | 0.9980    | 1.0    | 0.9990 | 0.9998   |
-| 0.0031        | 32.0  | 1600 | 0.0012          | 1.0       | 1.0    | 1.0    | 1.0      |
-| 0.0031        | 34.0  | 1700 | 0.0012          | 1.0       | 1.0    | 1.0    | 1.0      |
-| 0.0031        | 36.0  | 1800 | 0.0012          | 1.0       | 1.0    | 1.0    | 1.0      |
-| 0.0031        | 38.0  | 1900 | 0.0013          | 1.0       | 1.0    | 1.0    | 1.0      |
-| 0.0021        | 40.0  | 2000 | 0.0013          | 1.0       | 1.0    | 1.0    | 1.0      |
 
 
 ### Framework versions