update model card README.md

README.md

@@ -2,8 +2,6 @@
 license: cc-by-nc-sa-4.0
 tags:
 - generated_from_trainer
-datasets:
-- cord-layoutlmv3
 metrics:
 - precision
 - recall
@@ -11,29 +9,7 @@ metrics:
 - accuracy
 model-index:
 - name: layoutlmv3-finetuned-cord_100
-  results:
-  - task:
-      name: Token Classification
-      type: token-classification
-    dataset:
-      name: cord-layoutlmv3
-      type: cord-layoutlmv3
-      config: cord
-      split: test
-      args: cord
-    metrics:
-    - name: Precision
-      type: precision
-      value: 0.4079861111111111
-    - name: Recall
-      type: recall
-      value: 0.5276946107784432
-    - name: F1
-      type: f1
-      value: 0.46018276762402094
-    - name: Accuracy
-      type: accuracy
-      value: 0.40025466893039047
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -41,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # layoutlmv3-finetuned-cord_100
 
-This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the cord-layoutlmv3 dataset.
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.8382
-- Precision: 0.4080
-- Recall: 0.5277
-- F1: 0.4602
-- Accuracy: 0.4003
+- Loss: 0.6111
+- Precision: 0.8372
+- Recall: 0.8182
+- F1: 0.8276
+- Accuracy: 0.8730
 
 ## Model description
 
@@ -78,13 +54,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 0.33  | 50   | 3.1357          | 0.4186    | 0.5082 | 0.4591 | 0.3688   |
-| No log        | 0.67  | 100  | 2.8382          | 0.4080    | 0.5277 | 0.4602 | 0.4003   |
+| No log        | 3.33  | 50   | 0.8994          | 0.6667    | 0.5909 | 0.6265 | 0.7619   |
+| No log        | 6.67  | 100  | 0.6111          | 0.8372    | 0.8182 | 0.8276 | 0.8730   |
 
 
 ### Framework versions
 
-- Transformers 4.28.0
-- Pytorch 2.0.0+cu118
+- Transformers 4.29.2
+- Pytorch 2.0.1+cu118
 - Datasets 2.12.0
 - Tokenizers 0.13.3