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--- |
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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: Panant/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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# Panant/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: 0.2901 |
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- Validation Loss: 0.6709 |
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- Train Overall Precision: 0.7158 |
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- Train Overall Recall: 0.7973 |
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- Train Overall F1: 0.7543 |
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- Train Overall Accuracy: 0.8036 |
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- Epoch: 6 |
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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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| 1.6990 | 1.3937 | 0.2342 | 0.2454 | 0.2396 | 0.5233 | 0 | |
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| 1.1531 | 0.8728 | 0.5680 | 0.6327 | 0.5986 | 0.7422 | 1 | |
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| 0.7533 | 0.7316 | 0.6481 | 0.7200 | 0.6822 | 0.7642 | 2 | |
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| 0.5825 | 0.6844 | 0.6840 | 0.7592 | 0.7196 | 0.7896 | 3 | |
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| 0.4667 | 0.6354 | 0.7123 | 0.7812 | 0.7452 | 0.8108 | 4 | |
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| 0.3650 | 0.6304 | 0.7208 | 0.7797 | 0.7491 | 0.8153 | 5 | |
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| 0.2901 | 0.6709 | 0.7158 | 0.7973 | 0.7543 | 0.8036 | 6 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- TensorFlow 2.13.0 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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