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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# lilt-en-funsd

This model is a fine-tuned version of [SCUT-DLVCLab/lilt-roberta-en-base](https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base) on the funsd-layoutlmv3 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.9291
- eval_ANSWER: {'precision': 0.0166358595194085, 'recall': 0.044063647490820076, 'f1': 0.024152968802415294, 'number': 817}
- eval_HEADER: {'precision': 0.004098360655737705, 'recall': 0.008403361344537815, 'f1': 0.005509641873278237, 'number': 119}
- eval_QUESTION: {'precision': 0.08307501549907005, 'recall': 0.2488393686165274, 'f1': 0.12456425749477108, 'number': 1077}
- eval_overall_precision: 0.0541
- eval_overall_recall: 0.1515
- eval_overall_f1: 0.0798
- eval_overall_accuracy: 0.1625
- eval_runtime: 4.0045
- eval_samples_per_second: 12.486
- eval_steps_per_second: 1.748
- step: 0

## 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: 2500

### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1