layoutlmv3-finetuned-500

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

• Loss: 0.2173
• Precision: 0.6567
• Recall: 0.7311
• F1: 0.6919
• Accuracy: 0.9491

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: 5
• eval_batch_size: 5
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• training_steps: 2500

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	2.5	250	0.6612	0.1340	0.1849	0.1554	0.8477
0.8157	5.0	500	0.4681	0.3127	0.3809	0.3435	0.8876
0.8157	7.5	750	0.3601	0.3973	0.5049	0.4447	0.9125
0.3587	10.0	1000	0.2979	0.5004	0.5945	0.5434	0.9268
0.3587	12.5	1250	0.2673	0.5958	0.6660	0.6289	0.9386
0.2313	15.0	1500	0.2444	0.6228	0.7041	0.6610	0.9437
0.2313	17.5	1750	0.2317	0.6353	0.7185	0.6744	0.9453
0.1717	20.0	2000	0.2224	0.6527	0.7227	0.6859	0.9485
0.1717	22.5	2250	0.2191	0.6580	0.7255	0.6901	0.9481
0.145	25.0	2500	0.2173	0.6567	0.7311	0.6919	0.9491

Framework versions

• Transformers 4.48.3
• Pytorch 2.5.1+cu124
• Datasets 3.3.2
• Tokenizers 0.21.0