layout_lm_fine_tune_funsd_dataset

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: 0.2499
• Validation Loss: 0.6927
• Train Overall Precision: 0.7401
• Train Overall Recall: 0.8159
• Train Overall F1: 0.7761
• Train Overall Accuracy: 0.8046
• 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
1.7326	1.4249	0.2261	0.2052	0.2151	0.5250	0
1.1901	0.9108	0.5753	0.6207	0.5972	0.7156	1
0.7777	0.7170	0.6511	0.7396	0.6925	0.7679	2
0.5681	0.6626	0.6988	0.7777	0.7362	0.7920	3
0.4449	0.6512	0.7236	0.7762	0.7490	0.8013	4
0.3576	0.6547	0.7251	0.7888	0.7556	0.8073	5
0.2910	0.6700	0.7380	0.7958	0.7658	0.8106	6
0.2499	0.6927	0.7401	0.8159	0.7761	0.8046	7

Framework versions

• Transformers 4.28.1
• TensorFlow 2.12.0
• Datasets 2.11.0
• Tokenizers 0.13.3