lilt-en-funsd

This model is a fine-tuned version of SCUT-DLVCLab/lilt-roberta-en-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.9402
• Answer: {'precision': 0.4992163009404389, 'recall': 0.7796817625458996, 'f1': 0.608695652173913, 'number': 817}
• Header: {'precision': 0.03125, 'recall': 0.008403361344537815, 'f1': 0.013245033112582781, 'number': 119}
• Question: {'precision': 0.625, 'recall': 0.7753017641597029, 'f1': 0.692084542063821, 'number': 1077}
• Overall Precision: 0.5571
• Overall Recall: 0.7317
• Overall F1: 0.6326
• Overall Accuracy: 0.6359

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: 25
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.0