metadata

license: mit
base_model: SCUT-DLVCLab/lilt-roberta-en-base
tags:
  - generated_from_trainer
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 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