|
|
--- |
|
|
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: 1.5315 |
|
|
- Answer: {'precision': 0.03470437017994859, 'recall': 0.03337453646477132, 'f1': 0.03402646502835539, 'number': 809} |
|
|
- Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} |
|
|
- Question: {'precision': 0.3425827107790822, 'recall': 0.30140845070422534, 'f1': 0.32067932067932065, 'number': 1065} |
|
|
- Overall Precision: 0.2029 |
|
|
- Overall Recall: 0.1746 |
|
|
- Overall F1: 0.1877 |
|
|
- Overall Accuracy: 0.3869 |
|
|
|
|
|
## 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: 16 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 2 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Answer | Header | Question | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:| |
|
|
| 1.7866 | 1.0 | 10 | 1.6364 | {'precision': 0.014164305949008499, 'recall': 0.012360939431396786, 'f1': 0.0132013201320132, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.20684931506849316, 'recall': 0.14178403755868543, 'f1': 0.16824512534818942, 'number': 1065} | 0.1121 | 0.0808 | 0.0939 | 0.3375 | |
|
|
| 1.5665 | 2.0 | 20 | 1.5315 | {'precision': 0.03470437017994859, 'recall': 0.03337453646477132, 'f1': 0.03402646502835539, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.3425827107790822, 'recall': 0.30140845070422534, 'f1': 0.32067932067932065, 'number': 1065} | 0.2029 | 0.1746 | 0.1877 | 0.3869 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.28.0 |
|
|
- Pytorch 2.0.1+cu117 |
|
|
- Datasets 2.12.0 |
|
|
- Tokenizers 0.13.3 |
|
|
|
