layoutlm-cord-tf-colab

This model is a fine-tuned version of 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