ocr-scanner-v2 / README.md
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metadata
library_name: transformers
license: mit
base_model: microsoft/layoutlm-base-uncased
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
model-index:
  - name: layoutlm-receipts
    results: []

layoutlm-receipts

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

  • Loss: 0.2190
  • Precision: 0.2222
  • Recall: 0.4
  • F1: 0.2857

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: 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
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1
0.7275 1.0 8 0.8111 0.0 0.0 0.0
0.6014 2.0 16 0.6757 0.0 0.0 0.0
0.5061 3.0 24 0.5598 0.0 0.0 0.0
0.4025 4.0 32 0.4736 0.0 0.0 0.0
0.3486 5.0 40 0.4236 0.0571 0.1 0.0727
0.3318 6.0 48 0.3784 0.0377 0.1 0.0548
0.2649 7.0 56 0.3338 0.1064 0.25 0.1493
0.1982 8.0 64 0.2808 0.25 0.4 0.3077
0.1658 9.0 72 0.2388 0.1778 0.4 0.2462
0.1637 10.0 80 0.2190 0.2222 0.4 0.2857

Framework versions

  • Transformers 4.56.1
  • Pytorch 2.8.0+cu126
  • Datasets 4.0.0
  • Tokenizers 0.22.0