layoutlmv3-ap8_5_stitched_32_batch_5e5_1k

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: 0.0234
• Precision: 0.5263
• Recall: 0.625
• F1: 0.5714
• Accuracy: 0.9958

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: 32
• eval_batch_size: 32
• 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
No log	83.3333	250	0.0229	0.4762	0.625	0.5405	0.9953
0.1429	166.6667	500	0.0217	0.5263	0.625	0.5714	0.9956
0.1429	250.0	750	0.0234	0.5263	0.625	0.5714	0.9958
0.0008	333.3333	1000	0.0232	0.5556	0.625	0.5882	0.9958

Framework versions

• Transformers 4.50.0
• Pytorch 2.6.0+cu124
• Datasets 3.4.1
• Tokenizers 0.21.1