update model card README.md

README.md

@@ -3,7 +3,7 @@ license: cc-by-nc-sa-4.0
 tags:
 - generated_from_trainer
 datasets:
-- nielsr/funsd-layoutlmv3
+- pasha
 metrics:
 - precision
 - recall
@@ -16,24 +16,24 @@ model-index:
       name: Token Classification
       type: token-classification
     dataset:
-      name: nielsr/funsd-layoutlmv3
-      type: nielsr/funsd-layoutlmv3
+      name: pasha
+      type: pasha
       config: pasha
       split: test
       args: pasha
     metrics:
     - name: Precision
       type: precision
-      value: 0.879144385026738
+      value: 0.9845822875582646
     - name: Recall
       type: recall
-      value: 0.888328530259366
+      value: 0.989193083573487
     - name: F1
       type: f1
-      value: 0.8837125963089052
+      value: 0.9868823000898472
     - name: Accuracy
       type: accuracy
-      value: 0.909112825458052
+      value: 0.9908389585342333
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -41,13 +41,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # pasha
 
-This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the nielsr/funsd-layoutlmv3 dataset.
+This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the pasha dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6462
-- Precision: 0.8791
-- Recall: 0.8883
-- F1: 0.8837
-- Accuracy: 0.9091
+- Loss: 0.0558
+- Precision: 0.9846
+- Recall: 0.9892
+- F1: 0.9869
+- Accuracy: 0.9908
 
 ## Model description
 
@@ -72,13 +72,22 @@ 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: 100
+- training_steps: 1000
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 2.13  | 100  | 0.6462          | 0.8791    | 0.8883 | 0.8837 | 0.9091   |
+| No log        | 2.13  | 100  | 0.2662          | 0.9524    | 0.9442 | 0.9483 | 0.9566   |
+| No log        | 4.26  | 200  | 0.1026          | 0.9771    | 0.9820 | 0.9795 | 0.9851   |
+| No log        | 6.38  | 300  | 0.0722          | 0.9821    | 0.9878 | 0.9849 | 0.9884   |
+| No log        | 8.51  | 400  | 0.0608          | 0.9852    | 0.9863 | 0.9858 | 0.9892   |
+| 0.2962        | 10.64 | 500  | 0.0606          | 0.9849    | 0.9860 | 0.9854 | 0.9889   |
+| 0.2962        | 12.77 | 600  | 0.0518          | 0.9860    | 0.9910 | 0.9885 | 0.9920   |
+| 0.2962        | 14.89 | 700  | 0.0526          | 0.9864    | 0.9910 | 0.9887 | 0.9923   |
+| 0.2962        | 17.02 | 800  | 0.0543          | 0.9849    | 0.9896 | 0.9872 | 0.9913   |
+| 0.2962        | 19.15 | 900  | 0.0557          | 0.9846    | 0.9888 | 0.9867 | 0.9911   |
+| 0.0255        | 21.28 | 1000 | 0.0558          | 0.9846    | 0.9892 | 0.9869 | 0.9908   |
 
 
 ### Framework versions