<!-- 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 on the funsd-layoutlmv3 dataset. It achieves the following results on the evaluation set:
- Loss: 1.6511
- Answer: {'precision': 0.02037617554858934, 'recall': 0.01591187270501836, 'f1': 0.017869415807560136, 'number': 817}
- Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}
- Question: {'precision': 0.2322357019064125, 'recall': 0.1244196843082637, 'f1': 0.16203143893591293, 'number': 1077}
- Overall Precision: 0.1210
- Overall Recall: 0.0730
- Overall F1: 0.0911
- Overall Accuracy: 0.3745
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Answer | Header | Question | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|---|
| 1.8834 | 0.07 | 5 | 1.7075 | {'precision': 0.038461538461538464, 'recall': 0.0416156670746634, 'f1': 0.03997648442092886, 'number': 817} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.08, 'recall': 0.0018570102135561746, 'f1': 0.003629764065335753, 'number': 1077} | 0.0396 | 0.0179 | 0.0246 | 0.3295 |
| 1.7718 | 0.13 | 10 | 1.6511 | {'precision': 0.02037617554858934, 'recall': 0.01591187270501836, 'f1': 0.017869415807560136, 'number': 817} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.2322357019064125, 'recall': 0.1244196843082637, 'f1': 0.16203143893591293, 'number': 1077} | 0.1210 | 0.0730 | 0.0911 | 0.3745 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
