Layoutlmv3InvoiceCzechV03

This model is a fine-tuned version of TomasFAV/Layoutlmv3InvoiceCzechV0 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0415
  • Precision: 0.8985
  • Recall: 0.9289
  • F1: 0.9135
  • Accuracy: 0.9921

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: 8
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 0.1
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 23 0.1122 0.6618 0.7648 0.7096 0.9714
No log 2.0 46 0.0820 0.7325 0.8477 0.7859 0.9793
No log 3.0 69 0.0584 0.8167 0.8596 0.8376 0.9860
No log 4.0 92 0.0536 0.8323 0.9069 0.8680 0.9882
No log 5.0 115 0.0477 0.8390 0.9171 0.8763 0.9890
No log 6.0 138 0.0497 0.8717 0.8849 0.8783 0.9899
No log 7.0 161 0.0424 0.8549 0.9171 0.8849 0.9901
No log 8.0 184 0.0426 0.8728 0.9171 0.8944 0.9911
No log 9.0 207 0.0472 0.8799 0.9052 0.8924 0.9905
No log 10.0 230 0.0471 0.8704 0.9205 0.8947 0.9905
No log 11.0 253 0.0432 0.8860 0.9205 0.9029 0.9913
No log 12.0 276 0.0466 0.8861 0.9086 0.8972 0.9913
No log 13.0 299 0.0438 0.9003 0.9171 0.9086 0.9918
No log 14.0 322 0.0423 0.8831 0.9205 0.9014 0.9914
No log 15.0 345 0.0410 0.8916 0.9188 0.9050 0.9916
No log 16.0 368 0.0448 0.8947 0.9205 0.9074 0.9918
No log 17.0 391 0.0410 0.9010 0.9239 0.9123 0.9921
No log 18.0 414 0.0415 0.8985 0.9289 0.9135 0.9921
No log 19.0 437 0.0425 0.8962 0.9205 0.9082 0.9917
No log 20.0 460 0.0422 0.8962 0.9205 0.9082 0.9918

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2
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