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--- |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: layout_lm_fine_tune_funsd_dataset |
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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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# layout_lm_fine_tune_funsd_dataset |
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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: 0.2499 |
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- Validation Loss: 0.6927 |
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- Train Overall Precision: 0.7401 |
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- Train Overall Recall: 0.8159 |
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- Train Overall F1: 0.7761 |
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- Train Overall Accuracy: 0.8046 |
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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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| 1.7326 | 1.4249 | 0.2261 | 0.2052 | 0.2151 | 0.5250 | 0 | |
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| 1.1901 | 0.9108 | 0.5753 | 0.6207 | 0.5972 | 0.7156 | 1 | |
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| 0.7777 | 0.7170 | 0.6511 | 0.7396 | 0.6925 | 0.7679 | 2 | |
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| 0.5681 | 0.6626 | 0.6988 | 0.7777 | 0.7362 | 0.7920 | 3 | |
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| 0.4449 | 0.6512 | 0.7236 | 0.7762 | 0.7490 | 0.8013 | 4 | |
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| 0.3576 | 0.6547 | 0.7251 | 0.7888 | 0.7556 | 0.8073 | 5 | |
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| 0.2910 | 0.6700 | 0.7380 | 0.7958 | 0.7658 | 0.8106 | 6 | |
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| 0.2499 | 0.6927 | 0.7401 | 0.8159 | 0.7761 | 0.8046 | 7 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- TensorFlow 2.12.0 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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