|
--- |
|
license: cc-by-nc-sa-4.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- invoice_layoutlmv3 |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: layoutlmv3-finetuned-intellectai |
|
results: |
|
- task: |
|
name: Token Classification |
|
type: token-classification |
|
dataset: |
|
name: invoice_layoutlmv3 |
|
type: invoice_layoutlmv3 |
|
config: intellectai |
|
split: validation |
|
args: intellectai |
|
metrics: |
|
- name: Precision |
|
type: precision |
|
value: 0.7053571428571429 |
|
- name: Recall |
|
type: recall |
|
value: 0.8540540540540541 |
|
- name: F1 |
|
type: f1 |
|
value: 0.7726161369193154 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9624772313296903 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# layoutlmv3-finetuned-intellectai |
|
|
|
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the invoice_layoutlmv3 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3645 |
|
- Precision: 0.7054 |
|
- Recall: 0.8541 |
|
- F1: 0.7726 |
|
- Accuracy: 0.9625 |
|
|
|
## 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: 1e-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: 500 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 0.79 | 50 | 1.7979 | 0.0228 | 0.0541 | 0.0321 | 0.1410 | |
|
| No log | 1.59 | 100 | 1.2400 | 0.0863 | 0.4216 | 0.1433 | 0.2616 | |
|
| No log | 2.38 | 150 | 0.8691 | 0.1279 | 0.6919 | 0.2159 | 0.4495 | |
|
| No log | 3.17 | 200 | 0.6001 | 0.2323 | 0.8162 | 0.3617 | 0.7570 | |
|
| No log | 3.97 | 250 | 0.4709 | 0.4660 | 0.7784 | 0.5830 | 0.9093 | |
|
| No log | 4.76 | 300 | 0.3986 | 0.5977 | 0.8270 | 0.6939 | 0.9472 | |
|
| No log | 5.56 | 350 | 0.3762 | 0.5714 | 0.8216 | 0.6741 | 0.9454 | |
|
| No log | 6.35 | 400 | 0.3763 | 0.7048 | 0.8649 | 0.7767 | 0.9636 | |
|
| No log | 7.14 | 450 | 0.3696 | 0.6639 | 0.8541 | 0.7470 | 0.9570 | |
|
| 0.71 | 7.94 | 500 | 0.3645 | 0.7054 | 0.8541 | 0.7726 | 0.9625 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.27.1 |
|
- Pytorch 1.13.1+cu116 |
|
- Datasets 2.10.1 |
|
- Tokenizers 0.13.2 |
|
|
