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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: 0.6138 |
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- Validation Loss: 1.0719 |
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- Train Overall Precision: 0.4799 |
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- Train Overall Recall: 0.5926 |
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- Train Overall F1: 0.5303 |
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- Train Overall Accuracy: 0.6254 |
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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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| 1.6621 | 1.4563 | 0.1960 | 0.3126 | 0.2410 | 0.4075 | 0 | |
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| 1.3485 | 1.2456 | 0.2943 | 0.4867 | 0.3668 | 0.4838 | 1 | |
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| 1.1546 | 1.1675 | 0.3643 | 0.5334 | 0.4329 | 0.5295 | 2 | |
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| 1.0163 | 1.0992 | 0.4061 | 0.5514 | 0.4678 | 0.5842 | 3 | |
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| 0.8892 | 1.0781 | 0.4346 | 0.5605 | 0.4896 | 0.5989 | 4 | |
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| 0.7755 | 1.1893 | 0.4589 | 0.5735 | 0.5098 | 0.5913 | 5 | |
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| 0.6631 | 1.0950 | 0.4863 | 0.5595 | 0.5203 | 0.6265 | 6 | |
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| 0.6138 | 1.0719 | 0.4799 | 0.5926 | 0.5303 | 0.6254 | 7 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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