update model card README.md

README.md

@@ -4,9 +4,36 @@ tags:
 - generated_from_trainer
 datasets:
 - cne-layoutlmv3-data
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: layoutlmv3-finetuned-cne_100
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: cne-layoutlmv3-data
+      type: cne-layoutlmv3-data
+      config: cne-dataset
+      split: test
+      args: cne-dataset
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9950738916256158
+    - name: Recall
+      type: recall
+      value: 0.9950738916256158
+    - name: F1
+      type: f1
+      value: 0.9950738916256159
+    - name: Accuracy
+      type: accuracy
+      value: 0.9992716678805535
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,6 +42,12 @@ should probably proofread and complete it, then remove this comment. -->
 # layoutlmv3-finetuned-cne_100
 
 This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the cne-layoutlmv3-data dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0008
+- Precision: 0.9951
+- Recall: 0.9951
+- F1: 0.9951
+- Accuracy: 0.9993
 
 ## Model description
 
@@ -41,6 +74,22 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - training_steps: 2500
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 7.81  | 250  | 0.0028          | 0.9951    | 0.9951 | 0.9951 | 0.9993   |
+| 0.0229        | 15.62 | 500  | 0.0015          | 0.9951    | 0.9951 | 0.9951 | 0.9993   |
+| 0.0229        | 23.44 | 750  | 0.0011          | 0.9951    | 0.9951 | 0.9951 | 0.9993   |
+| 0.0031        | 31.25 | 1000 | 0.0009          | 0.9951    | 0.9951 | 0.9951 | 0.9993   |
+| 0.0031        | 39.06 | 1250 | 0.0009          | 0.9951    | 0.9951 | 0.9951 | 0.9993   |
+| 0.0019        | 46.88 | 1500 | 0.0008          | 0.9951    | 0.9951 | 0.9951 | 0.9993   |
+| 0.0019        | 54.69 | 1750 | 0.0008          | 0.9951    | 0.9951 | 0.9951 | 0.9993   |
+| 0.0014        | 62.5  | 2000 | 0.0008          | 0.9951    | 0.9951 | 0.9951 | 0.9993   |
+| 0.0014        | 70.31 | 2250 | 0.0008          | 0.9951    | 0.9951 | 0.9951 | 0.9993   |
+| 0.001         | 78.12 | 2500 | 0.0008          | 0.9951    | 0.9951 | 0.9951 | 0.9993   |
+
+
 ### Framework versions
 
 - Transformers 4.30.2