layoutlmv3-ap7_7_stitched_16_batch_2e5

This model is a fine-tuned version of microsoft/layoutlmv3-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0128
• Precision: 0.6897
• Recall: 0.8333
• F1: 0.7547
• Accuracy: 0.9977

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• 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
• lr_scheduler_warmup_ratio: 0.1
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.3926	50.0	250	0.0323	0.3929	0.4583	0.4231	0.9923
0.0112	100.0	500	0.0158	0.6667	0.75	0.7059	0.9967
0.0038	150.0	750	0.0128	0.6897	0.8333	0.7547	0.9977
0.0024	200.0	1000	0.0127	0.6897	0.8333	0.7547	0.9977

Framework versions

• Transformers 4.49.0
• Pytorch 2.6.0+cu124
• Datasets 3.4.1
• Tokenizers 0.21.1