| | ---
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| | library_name: transformers
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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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| |
|
| | <!-- This model card has been generated automatically according to the information Keras had access to. You should
|
| | 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: 0.2409
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| | - Validation Loss: 0.6905
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| | - Train Overall Precision: 0.7213
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| | - Train Overall Recall: 0.7858
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| | - Train Overall F1: 0.7522
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| | - Train Overall Accuracy: 0.7998
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| | - Epoch: 7
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| |
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| | ## Model description
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| |
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| | More information needed
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| |
|
| | ## Intended uses & limitations
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| |
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| | More information needed
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| |
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| | ## Training and evaluation data
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| |
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| | More information needed
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| |
|
| | ## Training procedure
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| |
|
| | ### Training hyperparameters
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| |
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| | The following hyperparameters were used during training:
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| | - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': np.float32(3e-05), 'decay': 0.0, 'beta_1': np.float32(0.9), 'beta_2': np.float32(0.999), 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
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| | - training_precision: mixed_float16
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| |
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| | ### Training results
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| |
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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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| | | 1.6885 | 1.3544 | 0.2506 | 0.2534 | 0.2520 | 0.5600 | 0 |
|
| | | 1.1672 | 0.8949 | 0.5489 | 0.5996 | 0.5731 | 0.7115 | 1 |
|
| | | 0.7766 | 0.7345 | 0.6327 | 0.7476 | 0.6854 | 0.7633 | 2 |
|
| | | 0.5690 | 0.6435 | 0.6684 | 0.7727 | 0.7168 | 0.7936 | 3 |
|
| | | 0.4387 | 0.6493 | 0.7180 | 0.7792 | 0.7474 | 0.7962 | 4 |
|
| | | 0.3470 | 0.6380 | 0.7147 | 0.7893 | 0.7501 | 0.8020 | 5 |
|
| | | 0.2901 | 0.6569 | 0.7317 | 0.7868 | 0.7582 | 0.8059 | 6 |
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| | | 0.2409 | 0.6905 | 0.7213 | 0.7858 | 0.7522 | 0.7998 | 7 |
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| |
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| |
|
| | ### Framework versions
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| |
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| | - Transformers 4.46.0
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| | - TensorFlow 2.18.0
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| | - Datasets 3.0.2
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| | - Tokenizers 0.20.1
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| | |
