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paper-cutting
hidonbush/paper-cutting
paper-cutting is a machine learning model from hidonbush. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- segformer
- Access
- Public
- Created
- Oct 30, 2024
- Updated
- Nov 1, 2024
- SHA
- dd5123f3
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
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
- Library
- transformers
- Type
- segformer
- Languages
- en, zh
- Created
- Oct 30, 2024
- Updated
- Nov 1, 2024