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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-funsd-sequence-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-sequence-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: 0.2348 |
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- Validation Loss: 0.6737 |
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- Train Overall Precision: 0.7356 |
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- Train Overall Recall: 0.7998 |
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- Train Overall F1: 0.7663 |
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- Train Overall Accuracy: 0.8220 |
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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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'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}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000} |
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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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| 1.7150 | 1.4139 | 0.2373 | 0.2860 | 0.2594 | 0.4954 | 0 | |
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| 1.1803 | 0.9205 | 0.5676 | 0.6322 | 0.5981 | 0.7008 | 1 | |
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| 0.7884 | 0.7100 | 0.6202 | 0.7250 | 0.6685 | 0.7735 | 2 | |
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| 0.5877 | 0.6476 | 0.6689 | 0.7662 | 0.7142 | 0.7942 | 3 | |
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| 0.4490 | 0.6179 | 0.7133 | 0.8078 | 0.7576 | 0.8066 | 4 | |
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| 0.3746 | 0.6305 | 0.7176 | 0.7878 | 0.7510 | 0.8129 | 5 | |
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| 0.3082 | 0.6924 | 0.7163 | 0.8018 | 0.7566 | 0.7937 | 6 | |
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| 0.2348 | 0.6737 | 0.7356 | 0.7998 | 0.7663 | 0.8220 | 7 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- TensorFlow 2.12.0 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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