| 
							 | 
						--- | 
					
					
						
						| 
							 | 
						base_model: microsoft/layoutlm-base-uncased | 
					
					
						
						| 
							 | 
						license: mit | 
					
					
						
						| 
							 | 
						tags: | 
					
					
						
						| 
							 | 
						- generated_from_keras_callback | 
					
					
						
						| 
							 | 
						model-index: | 
					
					
						
						| 
							 | 
						- name: layoutlm-cord-tf-colab | 
					
					
						
						| 
							 | 
						  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-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 | 
					
					
						
						| 
							 | 
						
 |