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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: 0.0418 |
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- Validation Loss: 0.1882 |
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- Train Overall Precision: 0.9468 |
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- Train Overall Recall: 0.9490 |
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- Train Overall F1: 0.9479 |
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- Train Overall Accuracy: 0.9652 |
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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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| 1.3129 | 0.5622 | 0.8065 | 0.8120 | 0.8093 | 0.8579 | 0 | |
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| 0.3927 | 0.2756 | 0.8965 | 0.8965 | 0.8965 | 0.9291 | 1 | |
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| 0.2136 | 0.1945 | 0.9233 | 0.9254 | 0.9244 | 0.9499 | 2 | |
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| 0.1335 | 0.1814 | 0.9363 | 0.9399 | 0.9381 | 0.9550 | 3 | |
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| 0.0915 | 0.1956 | 0.9390 | 0.9482 | 0.9436 | 0.9571 | 4 | |
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| 0.0810 | 0.2157 | 0.9392 | 0.9399 | 0.9395 | 0.9559 | 5 | |
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| 0.0628 | 0.1726 | 0.9410 | 0.9467 | 0.9439 | 0.9618 | 6 | |
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| 0.0418 | 0.1882 | 0.9468 | 0.9490 | 0.9479 | 0.9652 | 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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