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--- |
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library_name: transformers |
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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-SROIE-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-SROIE-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: 0.0151 |
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- Validation Loss: 0.0289 |
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- Train Overall Precision: 0.9110 |
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- Train Overall Recall: 0.9438 |
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- Train Overall F1: 0.9271 |
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- Train Overall Accuracy: 0.9942 |
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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': 2e-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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| 0.4238 | 0.1257 | 0.7483 | 0.6535 | 0.6977 | 0.9684 | 0 | |
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| 0.0943 | 0.0549 | 0.9101 | 0.7075 | 0.7961 | 0.9863 | 1 | |
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| 0.0500 | 0.0403 | 0.8310 | 0.8573 | 0.8440 | 0.9891 | 2 | |
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| 0.0344 | 0.0344 | 0.8468 | 0.9042 | 0.8746 | 0.9916 | 3 | |
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| 0.0282 | 0.0346 | 0.8417 | 0.9344 | 0.8856 | 0.9918 | 4 | |
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| 0.0222 | 0.0296 | 0.9155 | 0.9207 | 0.9181 | 0.9938 | 5 | |
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| 0.0168 | 0.0328 | 0.8756 | 0.9431 | 0.9081 | 0.9931 | 6 | |
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| 0.0151 | 0.0289 | 0.9110 | 0.9438 | 0.9271 | 0.9942 | 7 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- TensorFlow 2.18.0 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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