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UDOP-finetuned-DocLayNet-3

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

  • eval_loss: 0.7407
  • eval_precision: 0.6058
  • eval_recall: 0.5870
  • eval_f1: 0.5962
  • eval_accuracy: 0.7863
  • eval_runtime: 16.2128
  • eval_samples_per_second: 3.886
  • eval_steps_per_second: 1.974
  • epoch: 18.6
  • step: 800

Training procedure

Training code:

  https://github.com/mit1280/Document-AI/blob/main/UDOPEncoderModel_fine_tune_DocLayNet.ipynb

Inference code:

  https://github.com/mit1280/Document-AI/blob/main/UDOP_DocLayNet_Inference.ipynb

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 1000

Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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Dataset used to train Mit1208/UDOP-finetuned-DocLayNet