layoutlmv3-finetuned-funsd

This model is a fine-tuned version of microsoft/layoutlmv3-base on the nielsr/funsd-layoutlmv3 dataset. It achieves the following results on the evaluation set:

• Loss: 1.1164
• Precision: 0.9026
• Recall: 0.913
• F1: 0.9078
• Accuracy: 0.8330

The script for training can be found here: https://github.com/huggingface/transformers/tree/main/examples/research_projects/layoutlmv3

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:

• learning_rate: 1e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	10.0	100	0.5238	0.8366	0.886	0.8606	0.8410
No log	20.0	200	0.6930	0.8751	0.8965	0.8857	0.8322
No log	30.0	300	0.7784	0.8902	0.908	0.8990	0.8414
No log	40.0	400	0.9056	0.8916	0.905	0.8983	0.8364
0.2429	50.0	500	1.0016	0.8954	0.9075	0.9014	0.8298
0.2429	60.0	600	1.0097	0.8899	0.897	0.8934	0.8294
0.2429	70.0	700	1.0722	0.9035	0.9085	0.9060	0.8315
0.2429	80.0	800	1.0884	0.8905	0.9105	0.9004	0.8269
0.2429	90.0	900	1.1292	0.8938	0.909	0.9013	0.8279
0.0098	100.0	1000	1.1164	0.9026	0.913	0.9078	0.8330

Framework versions

• Transformers 4.19.0.dev0
• Pytorch 1.11.0+cu113
• Datasets 2.0.0
• Tokenizers 0.11.6