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--- |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: jinhybr/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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# jinhybr/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: 0.2987 |
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- Validation Loss: 0.6835 |
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- Train Overall Precision: 0.7270 |
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- Train Overall Recall: 0.7777 |
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- Train Overall F1: 0.7515 |
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- Train Overall Accuracy: 0.8056 |
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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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| 1.6886 | 1.4100 | 0.2324 | 0.2313 | 0.2318 | 0.5009 | 0 | |
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| 1.1702 | 0.8486 | 0.5971 | 0.6618 | 0.6278 | 0.7338 | 1 | |
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| 0.7521 | 0.7032 | 0.6561 | 0.7341 | 0.6929 | 0.7687 | 2 | |
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| 0.5727 | 0.6268 | 0.6736 | 0.7662 | 0.7169 | 0.7957 | 3 | |
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| 0.4586 | 0.6322 | 0.6909 | 0.7772 | 0.7315 | 0.7999 | 4 | |
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| 0.3725 | 0.6378 | 0.7134 | 0.7782 | 0.7444 | 0.8096 | 5 | |
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| 0.2987 | 0.6835 | 0.7270 | 0.7777 | 0.7515 | 0.8056 | 6 | |
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### Framework versions |
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- Transformers 4.23.1 |
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- TensorFlow 2.6.0 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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