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--- |
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license: mit |
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tags: |
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- generated_from_keras_callback |
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base_model: microsoft/layoutlm-base-uncased |
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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: 0.2479 |
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- Validation Loss: 0.6865 |
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- Train Overall Precision: 0.7469 |
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- Train Overall Recall: 0.8098 |
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- Train Overall F1: 0.7771 |
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- Train Overall Accuracy: 0.8111 |
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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': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': 2.9999999242136255e-05, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, '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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| 1.7068 | 1.4323 | 0.2302 | 0.2604 | 0.2444 | 0.5097 | 0 | |
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| 1.1785 | 0.8879 | 0.5487 | 0.6553 | 0.5973 | 0.7149 | 1 | |
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| 0.7570 | 0.7017 | 0.6315 | 0.7411 | 0.6819 | 0.7810 | 2 | |
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| 0.5598 | 0.6353 | 0.6893 | 0.7747 | 0.7295 | 0.7954 | 3 | |
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| 0.4407 | 0.6282 | 0.7144 | 0.7842 | 0.7477 | 0.8015 | 4 | |
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| 0.3450 | 0.6653 | 0.7174 | 0.7822 | 0.7484 | 0.8036 | 5 | |
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| 0.2758 | 0.7178 | 0.7002 | 0.7863 | 0.7407 | 0.7920 | 6 | |
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| 0.2479 | 0.6865 | 0.7469 | 0.8098 | 0.7771 | 0.8111 | 7 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- TensorFlow 2.13.1 |
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- Datasets 2.20.0 |
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- Tokenizers 0.15.2 |
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