|
--- |
|
license: cc-by-nc-sa-4.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- sroie |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: nexon_jan_2023 |
|
results: |
|
- task: |
|
name: Token Classification |
|
type: token-classification |
|
dataset: |
|
name: sroie |
|
type: sroie |
|
config: discharge |
|
split: test |
|
args: discharge |
|
metrics: |
|
- name: Precision |
|
type: precision |
|
value: 0.975609756097561 |
|
- name: Recall |
|
type: recall |
|
value: 0.9302325581395349 |
|
- name: F1 |
|
type: f1 |
|
value: 0.9523809523809524 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9971428571428571 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# nexon_jan_2023 |
|
|
|
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the sroie dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0380 |
|
- Precision: 0.9756 |
|
- Recall: 0.9302 |
|
- F1: 0.9524 |
|
- Accuracy: 0.9971 |
|
|
|
## 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: 1500 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 16.67 | 100 | 0.1998 | 0.6286 | 0.5116 | 0.5641 | 0.9571 | |
|
| No log | 33.33 | 200 | 0.0616 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| No log | 50.0 | 300 | 0.0439 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| No log | 66.67 | 400 | 0.0404 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| 0.1151 | 83.33 | 500 | 0.0389 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| 0.1151 | 100.0 | 600 | 0.0380 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| 0.1151 | 116.67 | 700 | 0.0378 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| 0.1151 | 133.33 | 800 | 0.0379 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| 0.1151 | 150.0 | 900 | 0.0378 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| 0.009 | 166.67 | 1000 | 0.0378 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| 0.009 | 183.33 | 1100 | 0.0378 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| 0.009 | 200.0 | 1200 | 0.0379 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| 0.009 | 216.67 | 1300 | 0.0379 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| 0.009 | 233.33 | 1400 | 0.0379 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
| 0.0064 | 250.0 | 1500 | 0.0380 | 0.9756 | 0.9302 | 0.9524 | 0.9971 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.27.0.dev0 |
|
- Pytorch 1.13.1+cu116 |
|
- Datasets 2.2.2 |
|
- Tokenizers 0.13.2 |
|
|
