paper-cutting

This model was a finetuned version of nvidia/mit-b5 on the paper-cutting datasetv0.1.

It was trained to extract body contents from any resources like articles and books, just like cutting them off the paper.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

paper-cutting v0.1

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 6e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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Dataset used to train hidonbush/paper-cutting