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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-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: 0.2471 |
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- Validation Loss: 0.6741 |
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- Train Overall Precision: 0.7311 |
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- Train Overall Recall: 0.7858 |
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- Train Overall F1: 0.7574 |
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- Train Overall Accuracy: 0.8104 |
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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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| 1.7162 | 1.4302 | 0.2735 | 0.3026 | 0.2873 | 0.4851 | 0 | |
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| 1.1601 | 0.8705 | 0.5728 | 0.6708 | 0.6180 | 0.7254 | 1 | |
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| 0.7538 | 0.7479 | 0.6533 | 0.7055 | 0.6784 | 0.7572 | 2 | |
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| 0.5704 | 0.6795 | 0.6686 | 0.7582 | 0.7106 | 0.7936 | 3 | |
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| 0.4379 | 0.6239 | 0.7022 | 0.7762 | 0.7374 | 0.8062 | 4 | |
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| 0.3470 | 0.6538 | 0.7226 | 0.7842 | 0.7522 | 0.7986 | 5 | |
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| 0.2908 | 0.6827 | 0.7033 | 0.7777 | 0.7386 | 0.7971 | 6 | |
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| 0.2471 | 0.6741 | 0.7311 | 0.7858 | 0.7574 | 0.8104 | 7 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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