--- base_model: microsoft/layoutlm-base-uncased license: mit tags: - generated_from_keras_callback model-index: - name: layoutlm-cord-tf-colab results: [] --- # layoutlm-cord-tf-colab 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: 0.0426 - Validation Loss: 0.1530 - Train Overall Precision: 0.9498 - Train Overall Recall: 0.9642 - Train Overall F1: 0.9569 - Train Overall Accuracy: 0.9669 - 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: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': 2.9999999242136255e-05, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000} - training_precision: mixed_float16 ### Training results | Train Loss | Validation Loss | Train Overall Precision | Train Overall Recall | Train Overall F1 | Train Overall Accuracy | Epoch | |:----------:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:----------------------:|:-----:| | 1.3249 | 0.5218 | 0.8344 | 0.8318 | 0.8331 | 0.8744 | 0 | | 0.4002 | 0.2680 | 0.9113 | 0.9148 | 0.9130 | 0.9334 | 1 | | 0.2153 | 0.2180 | 0.9062 | 0.9193 | 0.9127 | 0.9448 | 2 | | 0.1483 | 0.1840 | 0.9430 | 0.9437 | 0.9433 | 0.9610 | 3 | | 0.0940 | 0.1687 | 0.9383 | 0.9482 | 0.9432 | 0.9614 | 4 | | 0.0740 | 0.1539 | 0.9463 | 0.9528 | 0.9496 | 0.9665 | 5 | | 0.0600 | 0.1795 | 0.9355 | 0.9498 | 0.9426 | 0.9584 | 6 | | 0.0426 | 0.1530 | 0.9498 | 0.9642 | 0.9569 | 0.9669 | 7 | ### Framework versions - Transformers 4.41.2 - TensorFlow 2.15.0 - Datasets 2.20.0 - Tokenizers 0.19.1