metadata

license: mit
base_model: SCUT-DLVCLab/lilt-roberta-en-base
tags:
  - generated_from_trainer
datasets:
  - funsd-layoutlmv3
model-index:
  - name: lilt-en-funsd
    results: []

lilt-en-funsd

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: 1.2946
Answer: {'precision': 0.8767772511848341, 'recall': 0.9057527539779682, 'f1': 0.8910295003010236, 'number': 817}
Header: {'precision': 0.6106194690265486, 'recall': 0.5798319327731093, 'f1': 0.5948275862068966, 'number': 119}
Question: {'precision': 0.885766092475068, 'recall': 0.9071494893221913, 'f1': 0.8963302752293578, 'number': 1077}
Overall Precision: 0.8670
Overall Recall: 0.8872
Overall F1: 0.8770
Overall Accuracy: 0.8038

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
num_epochs: 4

Training results

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.3
Tokenizers 0.13.3