Create README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,38 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
language:
|
| 3 |
+
- ko
|
| 4 |
+
pipeline_tag: image-to-text
|
| 5 |
+
---
|
| 6 |
+
|
| 7 |
+
# **deplot_kr**
|
| 8 |
+
|
| 9 |
+
deplot_kr is a Image-to-Data(Text) model based on the google's pix2struct architecture.
|
| 10 |
+
It was fine-tuned from [DePlot](https://huggingface.co/google/deplot), using korean chart image-text pairs.
|
| 11 |
+
|
| 12 |
+
deplot_kr은 google의 pix2struct 구조를 기반으로 한 한국어 image-to-data(텍스트 형태의 데이터 테이블) 모델입니다.
|
| 13 |
+
[DePlot](https://huggingface.co/google/deplot) 모델을 한국어 차트 이미지-텍스트 쌍 데이터세트(30만 개)를 이용하여 fine-tuning 했습니다.
|
| 14 |
+
|
| 15 |
+
## How to use
|
| 16 |
+
|
| 17 |
+
'''python
|
| 18 |
+
>>> from transformers import Pix2StructImageProcessor()
|
| 19 |
+
|
| 20 |
+
|
| 21 |
+
### Training data
|
| 22 |
+
|
| 23 |
+
### Preprocessing
|
| 24 |
+
|
| 25 |
+
### Train
|
| 26 |
+
|
| 27 |
+
The model was trained in a TPU environment.
|
| 28 |
+
- num_warmup_steps : 1,000
|
| 29 |
+
- num_training_steps : 40,000
|
| 30 |
+
|
| 31 |
+
## Evaluation Results
|
| 32 |
+
|
| 33 |
+
This model achieves the following results:
|
| 34 |
+
|
| 35 |
+
|metrics name | % |
|
| 36 |
+
|:---:|:---:|
|
| 37 |
+
| RNSS (Relative Number Set Similarity)| 99.5483 |
|
| 38 |
+
| RMS F1 (Relative Mapping Similarity)| 16.6401 |
|