|
--- |
|
base_model: microsoft/layoutlm-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- funsd |
|
model-index: |
|
- name: layoutlm-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. --> |
|
|
|
# layoutlm-funsd |
|
|
|
This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the funsd dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.0638 |
|
- Answer: {'precision': 0.24285714285714285, 'recall': 0.21013597033374537, 'f1': 0.22531477799867464, 'number': 809} |
|
- Header: {'precision': 0.08695652173913043, 'recall': 0.01680672268907563, 'f1': 0.028169014084507043, 'number': 119} |
|
- Question: {'precision': 0.5682362330407024, 'recall': 0.6685446009389672, 'f1': 0.6143226919758413, 'number': 1065} |
|
- Overall Precision: 0.4474 |
|
- Overall Recall: 0.4436 |
|
- Overall F1: 0.4455 |
|
- Overall Accuracy: 0.6424 |
|
|
|
## 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: 3e-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 |
|
- num_epochs: 1 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Answer | Header | Question | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:| |
|
| 1.4448 | 1.0 | 75 | 1.0638 | {'precision': 0.24285714285714285, 'recall': 0.21013597033374537, 'f1': 0.22531477799867464, 'number': 809} | {'precision': 0.08695652173913043, 'recall': 0.01680672268907563, 'f1': 0.028169014084507043, 'number': 119} | {'precision': 0.5682362330407024, 'recall': 0.6685446009389672, 'f1': 0.6143226919758413, 'number': 1065} | 0.4474 | 0.4436 | 0.4455 | 0.6424 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.1 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|