| Full notebook: | |
| https://github.com/MustafaAlahmid/hugging_face_models/blob/main/layoutlm_funsd.ipynb | |
| --- | |
| tags: | |
| - generated_from_keras_callback | |
| model-index: | |
| - name: layoutlm-funsd-tf | |
| results: [] | |
| --- | |
| <!-- This model card has been generated automatically according to the information Keras had access to. You should | |
| probably proofread and complete it, then remove this comment. --> | |
| # layoutlm-funsd-tf | |
| This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Train Loss: 0.0691 | |
| - Validation Loss: 0.7709 | |
| - Train Overall Precision: 0.7410 | |
| - Train Overall Recall: 0.7953 | |
| - Train Overall F1: 0.7672 | |
| - Train Overall Accuracy: 0.8057 | |
| - Epoch: 7 | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - 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} | |
| - training_precision: mixed_float16 | |
| ### Training results | |
| | Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch | | |
| |:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:| | |
| | 1.1546 | 0.6939 | 0.6387 | 0.7381 | 0.6848 | 0.7761 | 0 | | |
| | 0.6170 | 0.5872 | 0.7099 | 0.7832 | 0.7448 | 0.7949 | 1 | | |
| | 0.4005 | 0.6761 | 0.6766 | 0.7777 | 0.7236 | 0.7729 | 2 | | |
| | 0.2921 | 0.6447 | 0.7169 | 0.7852 | 0.7495 | 0.7934 | 3 | | |
| | 0.2029 | 0.7472 | 0.7019 | 0.7953 | 0.7457 | 0.7852 | 4 | | |
| | 0.1383 | 0.7195 | 0.7327 | 0.7938 | 0.7620 | 0.8048 | 5 | | |
| | 0.0932 | 0.7851 | 0.7272 | 0.7998 | 0.7618 | 0.8063 | 6 | | |
| | 0.0691 | 0.7709 | 0.7410 | 0.7953 | 0.7672 | 0.8057 | 7 | | |
| ### Framework versions | |
| - Transformers 4.26.0 | |
| - TensorFlow 2.10.0 | |
| - Datasets 2.9.0 | |
| - Tokenizers 0.13.2 | |