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lilt-en-funsd-org – AI Model by tkazusa | AlphaNeural AI
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lilt-en-funsd-org
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transformers
pytorch
tensorboard
lilt
token-classification
generated_from_trainer
funsd-layoutlmv3
mit
autotrain_compatible
endpoints_compatible
us
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lilt-en-funsd-org
This model is a fine-tuned version of
SCUT-DLVCLab/lilt-roberta-en-base
on the funsd-layoutlmv3 dataset. It achieves the following results on the evaluation set:
Loss: 1.8428
Answer: {'precision': 0.047225501770956316, 'recall': 0.09791921664626684, 'f1': 0.06371963361210674, 'number': 817}
Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}
Question: {'precision': 0.08554412560909583, 'recall': 0.2934076137418756, 'f1': 0.13246698805281912, 'number': 1077}
Overall Precision: 0.0730
Overall Recall: 0.1967
Overall F1: 0.1065
Overall Accuracy: 0.2652
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: 5e-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
training_steps: 3
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.25.1
Pytorch 1.13.0+cu117
Datasets 2.7.1
Tokenizers 0.13.2
