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--- |
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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-ttform |
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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-ttform |
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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: 0.8035 |
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- Validation Loss: 0.6094 |
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- Train Overall Precision: 0.8793 |
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- Train Overall Recall: 0.7969 |
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- Train Overall F1: 0.8361 |
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- Train Overall Accuracy: 0.9204 |
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- Epoch: 7 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 3e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} |
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- training_precision: mixed_float16 |
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### Training results |
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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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| 1.9166 | 1.6851 | 0.125 | 0.1562 | 0.1389 | 0.6567 | 0 | |
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| 1.7084 | 1.4917 | 0.3793 | 0.3438 | 0.3607 | 0.7811 | 1 | |
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| 1.5343 | 1.3162 | 0.4151 | 0.3438 | 0.3761 | 0.7811 | 2 | |
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| 1.3620 | 1.1511 | 0.4528 | 0.375 | 0.4103 | 0.8159 | 3 | |
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| 1.2149 | 0.9970 | 0.5818 | 0.5 | 0.5378 | 0.8358 | 4 | |
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| 1.0742 | 0.8546 | 0.8393 | 0.7344 | 0.7833 | 0.8905 | 5 | |
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| 0.9422 | 0.7259 | 0.8393 | 0.7344 | 0.7833 | 0.9154 | 6 | |
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| 0.8035 | 0.6094 | 0.8793 | 0.7969 | 0.8361 | 0.9204 | 7 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- TensorFlow 2.9.2 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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