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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: 0.5754 |
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- Validation Loss: 1.0073 |
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- Train Overall Precision: 0.4858 |
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- Train Overall Recall: 0.5735 |
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- Train Overall F1: 0.5260 |
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- Train Overall Accuracy: 0.6411 |
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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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| 1.6595 | 1.4718 | 0.1431 | 0.2780 | 0.1889 | 0.4016 | 0 | |
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| 1.3342 | 1.2762 | 0.2962 | 0.4942 | 0.3704 | 0.4644 | 1 | |
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| 1.1464 | 1.1828 | 0.3753 | 0.5173 | 0.4350 | 0.5034 | 2 | |
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| 1.0198 | 1.0195 | 0.4070 | 0.5359 | 0.4626 | 0.6167 | 3 | |
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| 0.8729 | 1.0543 | 0.4343 | 0.5740 | 0.4945 | 0.6018 | 4 | |
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| 0.7979 | 1.2603 | 0.4648 | 0.5866 | 0.5186 | 0.5615 | 5 | |
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| 0.6799 | 1.0257 | 0.5180 | 0.5775 | 0.5461 | 0.6408 | 6 | |
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| 0.5754 | 1.0073 | 0.4858 | 0.5735 | 0.5260 | 0.6411 | 7 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- TensorFlow 2.10.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.13.2 |
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