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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-l |
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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-l |
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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: 0.2621 |
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- Validation Loss: 0.6925 |
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- Train Overall Precision: 0.7431 |
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- Train Overall Recall: 0.7822 |
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- Train Overall F1: 0.7622 |
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- Train Overall Accuracy: 0.8060 |
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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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| 1.6855 | 1.4048 | 0.2655 | 0.2945 | 0.2793 | 0.5163 | 0 | |
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| 1.1539 | 0.8468 | 0.6205 | 0.6548 | 0.6372 | 0.7410 | 1 | |
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| 0.7523 | 0.7215 | 0.6573 | 0.7516 | 0.7013 | 0.7662 | 2 | |
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| 0.5749 | 0.6737 | 0.6735 | 0.7536 | 0.7113 | 0.7868 | 3 | |
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| 0.4482 | 0.6720 | 0.7027 | 0.7792 | 0.7390 | 0.7917 | 4 | |
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| 0.3695 | 0.6387 | 0.7142 | 0.7948 | 0.7523 | 0.8047 | 5 | |
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| 0.3123 | 0.6608 | 0.7443 | 0.7958 | 0.7692 | 0.8154 | 6 | |
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| 0.2621 | 0.6925 | 0.7431 | 0.7822 | 0.7622 | 0.8060 | 7 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- TensorFlow 2.16.1 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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