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--- |
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license: mit |
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tags: |
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- generated_from_keras_callback |
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base_model: microsoft/layoutlm-base-uncased |
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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: 0.6164 |
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- Validation Loss: 1.0914 |
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- Train Overall Precision: 0.4921 |
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- Train Overall Recall: 0.5178 |
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- Train Overall F1: 0.5046 |
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- Train Overall Accuracy: 0.6136 |
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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: float32 |
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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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| 1.6889 | 1.4840 | 0.1755 | 0.3307 | 0.2293 | 0.3586 | 0 | |
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| 1.3467 | 1.2410 | 0.3182 | 0.4827 | 0.3836 | 0.4680 | 1 | |
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| 1.1412 | 1.1634 | 0.3303 | 0.5028 | 0.3986 | 0.5209 | 2 | |
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| 1.0429 | 1.1068 | 0.3727 | 0.5289 | 0.4373 | 0.5592 | 3 | |
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| 0.8937 | 1.0652 | 0.4460 | 0.5569 | 0.4953 | 0.6060 | 4 | |
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| 0.7579 | 1.0765 | 0.4660 | 0.5640 | 0.5103 | 0.5983 | 5 | |
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| 0.7126 | 1.1322 | 0.4677 | 0.5845 | 0.5196 | 0.6209 | 6 | |
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| 0.6164 | 1.0914 | 0.4921 | 0.5178 | 0.5046 | 0.6136 | 7 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- TensorFlow 2.15.0 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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