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paper-cutting – AI Model by hidonbush | AlphaNeural AI
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hidonbush
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paper-cutting
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transformers
tensorboard
safetensors
segformer
generated_from_trainer
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zh
hidonbush/paper-cuttingv0.1
nvidia/mit-b5
finetune
endpoints_compatible
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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
