End of training

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.0
+      value: 0.0026246719160104987
     - name: Recall
       type: recall
-      value: 0.0
+      value: 0.002028397565922921
     - name: F1
       type: f1
-      value: 0.0
+      value: 0.002288329519450801
     - name: Accuracy
       type: accuracy
-      value: 0.7722772277227723
+      value: 0.829155255951127
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ 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: 2.1181
-- Precision: 0.0
-- Recall: 0.0
-- F1: 0.0
-- Accuracy: 0.7723
+- Loss: 2.1347
+- Precision: 0.0026
+- Recall: 0.0020
+- F1: 0.0023
+- Accuracy: 0.8292
 
 ## Model description
 
@@ -77,9 +77,9 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
-| No log        | 0.1   | 5    | 2.1181          | 0.0       | 0.0    | 0.0 | 0.7723   |
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.1   | 5    | 2.1347          | 0.0026    | 0.0020 | 0.0023 | 0.8292   |
 
 
 ### Framework versions

model.safetensors

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training_args.bin

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