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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-cord-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-cord-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: 0.0379 |
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- Validation Loss: 0.1673 |
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- Train Overall Precision: 0.9428 |
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- Train Overall Recall: 0.9528 |
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- Train Overall F1: 0.9478 |
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- Train Overall Accuracy: 0.9605 |
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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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| 1.2812 | 0.5563 | 0.8209 | 0.8265 | 0.8237 | 0.8574 | 0 | |
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| 0.3842 | 0.2602 | 0.9121 | 0.9155 | 0.9138 | 0.9406 | 1 | |
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| 0.2075 | 0.2085 | 0.9257 | 0.9201 | 0.9229 | 0.9453 | 2 | |
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| 0.1377 | 0.1793 | 0.9368 | 0.9368 | 0.9368 | 0.9555 | 3 | |
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| 0.0889 | 0.1902 | 0.9282 | 0.9346 | 0.9314 | 0.9525 | 4 | |
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| 0.0747 | 0.1610 | 0.9455 | 0.9513 | 0.9484 | 0.9648 | 5 | |
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| 0.0514 | 0.1796 | 0.9480 | 0.9566 | 0.9523 | 0.9639 | 6 | |
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| 0.0379 | 0.1673 | 0.9428 | 0.9528 | 0.9478 | 0.9605 | 7 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- TensorFlow 2.16.1 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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