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--- |
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license: mit |
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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: layoutlm-funsd-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-funsd-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: 0.5535 |
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- Validation Loss: 1.2985 |
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- Train Overall Precision: 0.4855 |
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- Train Overall Recall: 0.5705 |
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- Train Overall F1: 0.5246 |
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- Train Overall Accuracy: 0.6026 |
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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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| 1.6900 | 1.4644 | 0.1772 | 0.1922 | 0.1844 | 0.4144 | 0 | |
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| 1.3402 | 1.2155 | 0.2920 | 0.4566 | 0.3562 | 0.4865 | 1 | |
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| 1.1357 | 1.1454 | 0.3449 | 0.4952 | 0.4066 | 0.5503 | 2 | |
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| 1.0088 | 1.1098 | 0.3871 | 0.5198 | 0.4438 | 0.5737 | 3 | |
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| 0.8868 | 1.0295 | 0.4061 | 0.5569 | 0.4697 | 0.6159 | 4 | |
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| 0.7747 | 1.1882 | 0.4507 | 0.5625 | 0.5004 | 0.6062 | 5 | |
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| 0.6577 | 1.0658 | 0.4760 | 0.5625 | 0.5156 | 0.6305 | 6 | |
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| 0.5535 | 1.2985 | 0.4855 | 0.5705 | 0.5246 | 0.6026 | 7 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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