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End of training

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  1. README.md +14 -20
  2. model.safetensors +1 -1
README.md CHANGED
@@ -25,16 +25,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.9979716024340771
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  - name: Recall
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  type: recall
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- value: 0.9979716024340771
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  - name: F1
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  type: f1
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- value: 0.9979716024340771
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  - name: Accuracy
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  type: accuracy
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- value: 0.9997893406361913
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  ---
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  <!-- 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. -->
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  This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the generated dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0040
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- - Precision: 0.9980
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- - Recall: 0.9980
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- - F1: 0.9980
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- - Accuracy: 0.9998
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  ## Model description
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@@ -73,22 +73,16 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - training_steps: 1000
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 100 | 0.1249 | 0.796 | 0.8073 | 0.8016 | 0.9785 |
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- | No log | 2.0 | 200 | 0.0338 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
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- | No log | 3.0 | 300 | 0.0194 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
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- | No log | 4.0 | 400 | 0.0153 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
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- | 0.1446 | 5.0 | 500 | 0.0126 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
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- | 0.1446 | 6.0 | 600 | 0.0102 | 0.9739 | 0.9858 | 0.9798 | 0.9973 |
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- | 0.1446 | 7.0 | 700 | 0.0065 | 0.9959 | 0.9939 | 0.9949 | 0.9994 |
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- | 0.1446 | 8.0 | 800 | 0.0045 | 0.9959 | 0.9959 | 0.9959 | 0.9996 |
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- | 0.1446 | 9.0 | 900 | 0.0052 | 0.9960 | 0.9980 | 0.9970 | 0.9996 |
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- | 0.0103 | 10.0 | 1000 | 0.0040 | 0.9980 | 0.9980 | 0.9980 | 0.9998 |
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  ### Framework versions
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 1.0
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  - name: Recall
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  type: recall
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+ value: 1.0
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  - name: F1
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  type: f1
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+ value: 1.0
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  - name: Accuracy
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  type: accuracy
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+ value: 1.0
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the generated dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0013
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+ - Precision: 1.0
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+ - Recall: 1.0
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+ - F1: 1.0
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+ - Accuracy: 1.0
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - training_steps: 2000
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.144 | 5.0 | 500 | 0.0124 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
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+ | 0.0081 | 10.0 | 1000 | 0.0042 | 0.9960 | 0.9980 | 0.9970 | 0.9996 |
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+ | 0.0034 | 15.0 | 1500 | 0.0013 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0023 | 20.0 | 2000 | 0.0018 | 0.9980 | 1.0 | 0.9990 | 0.9998 |
 
 
 
 
 
 
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  ### Framework versions
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