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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: Matt6450/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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# Matt6450/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: 0.2719 |
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- Validation Loss: 0.6616 |
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- Train Overall Precision: 0.7394 |
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- Train Overall Recall: 0.7858 |
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- Train Overall F1: 0.7619 |
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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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| 1.6975 | 1.4623 | 0.2206 | 0.2464 | 0.2328 | 0.4665 | 0 | |
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| 1.1784 | 0.8850 | 0.5696 | 0.6754 | 0.6180 | 0.7376 | 1 | |
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| 0.7831 | 0.7326 | 0.6444 | 0.7511 | 0.6937 | 0.7690 | 2 | |
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| 0.5823 | 0.6434 | 0.7028 | 0.7642 | 0.7322 | 0.7930 | 3 | |
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| 0.4477 | 0.6255 | 0.7062 | 0.7998 | 0.7501 | 0.8006 | 4 | |
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| 0.3644 | 0.6378 | 0.7339 | 0.7903 | 0.7611 | 0.8174 | 5 | |
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| 0.3135 | 0.6776 | 0.7324 | 0.7787 | 0.7549 | 0.8006 | 6 | |
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| 0.2719 | 0.6616 | 0.7394 | 0.7858 | 0.7619 | 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 0.15.1 |
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