layoutlmv3-large-cord

This model is a fine-tuned version of microsoft/layoutlmv3-large on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1616
• Precision: 0.9526
• Recall: 0.9482
• F1: 0.9504
• Accuracy: 0.9677

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: 5e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.25	100	0.5321	0.7584	0.7859	0.7719	0.8224
No log	0.5	200	0.4949	0.8091	0.8354	0.8221	0.8683
No log	0.75	300	0.3478	0.8668	0.8648	0.8658	0.8916
No log	1.0	400	0.5194	0.75	0.7117	0.7304	0.8513
0.6065	1.25	500	0.3052	0.9059	0.9003	0.9031	0.9341
0.6065	1.5	600	0.2427	0.9245	0.9173	0.9209	0.9443
0.6065	1.75	700	0.2372	0.9174	0.9181	0.9177	0.9477
0.6065	2.0	800	0.2044	0.9247	0.9212	0.9230	0.9494
0.6065	2.25	900	0.1847	0.9442	0.9413	0.9427	0.9613
0.1862	2.5	1000	0.1616	0.9526	0.9482	0.9504	0.9677

Framework versions

• Transformers 4.36.0
• Pytorch 2.0.0
• Datasets 2.16.1
• Tokenizers 0.15.0