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layoutlmv3-custom_no_text – AI Model by uttam333 | AlphaNeural AI
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layoutlmv3-custom_no_text
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transformers
tensorboard
safetensors
layoutlmv3
token-classification
generated_from_trainer
microsoft/layoutlm-base-uncased
finetune
mit
autotrain_compatible
endpoints_compatible
us
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layoutlmv3-custom_no_text
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:
eval_loss: 0.2406
eval_noise: {'precision': 0.772093023255814, 'recall': 0.8019323671497585, 'f1': 0.7867298578199052, 'number': 621}
eval_signal: {'precision': 0.7472868217054264, 'recall': 0.77491961414791, 'f1': 0.7608524072612471, 'number': 622}
eval_overall_precision: 0.7597
eval_overall_recall: 0.7884
eval_overall_f1: 0.7738
eval_overall_accuracy: 0.9518
eval_runtime: 1.0449
eval_samples_per_second: 34.452
eval_steps_per_second: 4.785
epoch: 19.0
step: 342
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: 3e-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
mixed_precision_training: Native AMP
Framework versions
Transformers 4.36.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0
