update model card README.md

README.md

@@ -8,22 +8,22 @@ metrics:
 - f1
 - accuracy
 model-index:
-- name: layoutlmv3-finetuned-funsd2
+- name: layoutlmv3-finetuned-funsd
   results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# layoutlmv3-finetuned-funsd2
+# layoutlmv3-finetuned-funsd
 
 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: 0.6187
-- Precision: 0.8757
-- Recall: 0.9055
-- F1: 0.8904
-- Accuracy: 0.8437
+- Loss: 0.6416
+- Precision: 0.8820
+- Recall: 0.908
+- F1: 0.8948
+- Accuracy: 0.8486
 
 ## Model description
 
@@ -43,8 +43,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 4
-- eval_batch_size: 16
+- train_batch_size: 10
+- eval_batch_size: 10
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -54,16 +54,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.32  | 50   | 0.9063          | 0.7006    | 0.757  | 0.7277 | 0.7607   |
-| No log        | 2.63  | 100  | 0.6387          | 0.7930    | 0.858  | 0.8242 | 0.7967   |
-| No log        | 3.95  | 150  | 0.5691          | 0.8171    | 0.8825 | 0.8486 | 0.8254   |
-| No log        | 5.26  | 200  | 0.5723          | 0.8315    | 0.881  | 0.8555 | 0.8223   |
-| No log        | 6.58  | 250  | 0.5897          | 0.8475    | 0.9    | 0.8729 | 0.8292   |
-| No log        | 7.89  | 300  | 0.6122          | 0.8482    | 0.9025 | 0.8745 | 0.8283   |
-| No log        | 9.21  | 350  | 0.6045          | 0.8505    | 0.899  | 0.8741 | 0.8392   |
-| No log        | 10.53 | 400  | 0.5662          | 0.8708    | 0.9    | 0.8852 | 0.8446   |
-| No log        | 11.84 | 450  | 0.5973          | 0.8739    | 0.9045 | 0.8889 | 0.8437   |
-| 0.4305        | 13.16 | 500  | 0.6187          | 0.8757    | 0.9055 | 0.8904 | 0.8437   |
+| No log        | 3.33  | 50   | 0.7810          | 0.7547    | 0.8155 | 0.7839 | 0.7633   |
+| No log        | 6.67  | 100  | 0.5576          | 0.8015    | 0.8805 | 0.8392 | 0.8060   |
+| No log        | 10.0  | 150  | 0.5810          | 0.8452    | 0.887  | 0.8656 | 0.8223   |
+| No log        | 13.33 | 200  | 0.5634          | 0.8498    | 0.8965 | 0.8725 | 0.8393   |
+| No log        | 16.67 | 250  | 0.5419          | 0.8814    | 0.907  | 0.8940 | 0.8529   |
+| No log        | 20.0  | 300  | 0.5817          | 0.8760    | 0.9005 | 0.8881 | 0.8465   |
+| No log        | 23.33 | 350  | 0.6015          | 0.8744    | 0.9085 | 0.8911 | 0.8429   |
+| No log        | 26.67 | 400  | 0.5982          | 0.8830    | 0.917  | 0.8997 | 0.8536   |
+| No log        | 30.0  | 450  | 0.6316          | 0.8832    | 0.907  | 0.8949 | 0.8493   |
+| 0.2944        | 33.33 | 500  | 0.6416          | 0.8820    | 0.908  | 0.8948 | 0.8486   |
 
 
 ### Framework versions