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Upload TFLayoutLMForTokenClassification

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  1. README.md +16 -9
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -4,24 +4,24 @@ base_model: microsoft/layoutlm-base-uncased
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  tags:
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  - generated_from_keras_callback
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  model-index:
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- - name: cor-c/layoutlm-invoice-tf
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information Keras had access to. You should
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  probably proofread and complete it, then remove this comment. -->
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- # cor-c/layoutlm-invoice-tf
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  This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 2.3852
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- - Validation Loss: 2.0674
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- - Train Overall Precision: 0.0
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- - Train Overall Recall: 0.0
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- - Train Overall F1: 0.0
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- - Train Overall Accuracy: 0.2968
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- - Epoch: 0
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  ## Model description
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@@ -48,6 +48,13 @@ The following hyperparameters were used during training:
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  | Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch |
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  |:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
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  | 2.3852 | 2.0674 | 0.0 | 0.0 | 0.0 | 0.2968 | 0 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  tags:
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  - generated_from_keras_callback
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  model-index:
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+ - name: layoutlm-invoice-tf
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information Keras had access to. You should
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  probably proofread and complete it, then remove this comment. -->
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+ # layoutlm-invoice-tf
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  This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.2904
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+ - Validation Loss: 0.3563
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+ - Train Overall Precision: 0.5792
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+ - Train Overall Recall: 0.5340
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+ - Train Overall F1: 0.5557
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+ - Train Overall Accuracy: 0.8995
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+ - Epoch: 7
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  ## Model description
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  | Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch |
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  |:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:|
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  | 2.3852 | 2.0674 | 0.0 | 0.0 | 0.0 | 0.2968 | 0 |
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+ | 1.8171 | 1.5521 | 0.0108 | 0.0202 | 0.0141 | 0.5448 | 1 |
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+ | 1.3443 | 1.1118 | 0.0736 | 0.1108 | 0.0884 | 0.6812 | 2 |
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+ | 0.9892 | 0.8281 | 0.1794 | 0.2191 | 0.1973 | 0.7733 | 3 |
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+ | 0.7126 | 0.6356 | 0.3009 | 0.3199 | 0.3101 | 0.8324 | 4 |
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+ | 0.5465 | 0.4954 | 0.4051 | 0.3980 | 0.4015 | 0.8606 | 5 |
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+ | 0.3916 | 0.4266 | 0.4813 | 0.4534 | 0.4669 | 0.8778 | 6 |
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+ | 0.2904 | 0.3563 | 0.5792 | 0.5340 | 0.5557 | 0.8995 | 7 |
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  ### Framework versions
tf_model.h5 CHANGED
@@ -1,3 +1,3 @@
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  size 450850760
 
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  version https://git-lfs.github.com/spec/v1
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  size 450850760