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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: 0.2552 |
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- Validation Loss: 0.6563 |
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- Train Overall Precision: 0.7174 |
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- Train Overall Recall: 0.7988 |
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- Train Overall F1: 0.7559 |
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- Train Overall Accuracy: 0.8073 |
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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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| 1.7065 | 1.3937 | 0.2463 | 0.2418 | 0.2441 | 0.5476 | 0 | |
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| 1.1571 | 0.8921 | 0.6122 | 0.6352 | 0.6235 | 0.7318 | 1 | |
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| 0.7498 | 0.6885 | 0.6740 | 0.7376 | 0.7044 | 0.7816 | 2 | |
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| 0.5523 | 0.6299 | 0.6752 | 0.7852 | 0.7260 | 0.8011 | 3 | |
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| 0.4503 | 0.6387 | 0.6913 | 0.7943 | 0.7392 | 0.8010 | 4 | |
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| 0.3554 | 0.6279 | 0.7121 | 0.7792 | 0.7441 | 0.8110 | 5 | |
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| 0.3005 | 0.6507 | 0.7201 | 0.7782 | 0.7480 | 0.8085 | 6 | |
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| 0.2552 | 0.6563 | 0.7174 | 0.7988 | 0.7559 | 0.8073 | 7 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- TensorFlow 2.12.0 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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