
# mt5-cpe-kmutt-thai-sentence-sum
This repository contains the finetuned mT5-base model for Thai sentence summarization. The architecture of the model is based on mT5 model and fine-tuned on text-summarization pairs in Thai.  Also, this project is a Senior Project of Computer Engineering Student at King Mongkut’s University of Technology Thonburi.

## Usage on SimpleTransformer (Tested on version 0.63.4)
```python
from simpletransformers.t5 import T5Model, T5Args
from torch import cuda

model = T5Model("t5", "thanathorn/mt5-cpe-kmutt-thai-sentence-sum", use_cuda=cuda.is_available())

sentence = "simplify: ถ้าพูดถึงขนมหวานในตำนานที่ชื่นใจที่สุดแล้วละก็ต้องไม่พ้น น้ำแข็งใส แน่เพราะว่าเป็นอะไรที่ชื่นใจสุด"
prediction = model.predict([sentence])
print(prediction[0])
```
(See the example on <a href="https://colab.research.google.com/drive/1XiNkZLgy1USwHYFVf_nEzOSWbHGSnYdg?usp=sharing">Google Colab</a>)

### Score
<ul>
  <li>ROUGE-1: 61.7805</li>
  <li>ROUGE-2: 45.9689</li>
  <li>ROUGE-L: 59.3542</li>
</ul>

### Intended uses & limitations
<ul>
  <li>You can use this model for Thai sentence text summarization.</li>
  <li>Not intended to use with paragraph text.</li>
</ul>
{"language": ["th"], "tags": ["summarization", "mT5"], "widget": [{"text": "simplify: \u0e16\u0e49\u0e32\u0e1e\u0e39\u0e14\u0e16\u0e36\u0e07\u0e02\u0e19\u0e21\u0e2b\u0e27\u0e32\u0e19\u0e43\u0e19\u0e15\u0e33\u0e19\u0e32\u0e19\u0e17\u0e35\u0e48\u0e0a\u0e37\u0e48\u0e19\u0e43\u0e08\u0e17\u0e35\u0e48\u0e2a\u0e38\u0e14\u0e41\u0e25\u0e49\u0e27\u0e25\u0e30\u0e01\u0e47\u0e15\u0e49\u0e2d\u0e07\u0e44\u0e21\u0e48\u0e1e\u0e49\u0e19 \u0e19\u0e49\u0e33\u0e41\u0e02\u0e47\u0e07\u0e43\u0e2a \u0e41\u0e19\u0e48\u0e40\u0e1e\u0e23\u0e32\u0e30\u0e27\u0e48\u0e32\u0e40\u0e1b\u0e47\u0e19\u0e2d\u0e30\u0e44\u0e23\u0e17\u0e35\u0e48\u0e0a\u0e37\u0e48\u0e19\u0e43\u0e08\u0e2a\u0e38\u0e14"}]}
transformers pytorch mt5 text2text-generation summarization mT5 th autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #mt5 #text2text-generation #summarization #mT5 #th #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 


# mt5-cpe-kmutt-thai-sentence-sum
This repository contains the finetuned mT5-base model for Thai sentence summarization. The architecture of the model is based on mT5 model and fine-tuned on text-summarization pairs in Thai.  Also, this project is a Senior Project of Computer Engineering Student at King Mongkut’s University of Technology Thonburi.

## Usage on SimpleTransformer (Tested on version 0.63.4)

(See the example on <a href="URL Colab</a>)

### Score
<ul>
  <li>ROUGE-1: 61.7805</li>
  <li>ROUGE-2: 45.9689</li>
  <li>ROUGE-L: 59.3542</li>
</ul>

### Intended uses & limitations
<ul>
  <li>You can use this model for Thai sentence text summarization.</li>
  <li>Not intended to use with paragraph text.</li>
</ul>
# mt5-cpe-kmutt-thai-sentence-sum
This repository contains the finetuned mT5-base model for Thai sentence summarization. The architecture of the model is based on mT5 model and fine-tuned on text-summarization pairs in Thai.  Also, this project is a Senior Project of Computer Engineering Student at King Mongkut’s University of Technology Thonburi. ## Usage on SimpleTransformer (Tested on version 0.63.4)

(See the example on <a href="URL Colab</a>) ### Score
<ul>
  <li>ROUGE-1: 61.7805</li>
  <li>ROUGE-2: 45.9689</li>
  <li>ROUGE-L: 59.3542</li>
</ul> ### Intended uses & limitations
<ul>
  <li>You can use this model for Thai sentence text summarization.</li>
  <li>Not intended to use with paragraph text.</li>
</ul>
TAGS
#transformers #pytorch #mt5 #text2text-generation #summarization #mT5 #th #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 # mt5-cpe-kmutt-thai-sentence-sum
This repository contains the finetuned mT5-base model for Thai sentence summarization. The architecture of the model is based on mT5 model and fine-tuned on text-summarization pairs in Thai.  Also, this project is a Senior Project of Computer Engineering Student at King Mongkut’s University of Technology Thonburi. ## Usage on SimpleTransformer (Tested on version 0.63.4)

(See the example on <a href="URL Colab</a>) ### Score
<ul>
  <li>ROUGE-1: 61.7805</li>
  <li>ROUGE-2: 45.9689</li>
  <li>ROUGE-L: 59.3542</li>
</ul> ### Intended uses & limitations
<ul>
  <li>You can use this model for Thai sentence text summarization.</li>
  <li>Not intended to use with paragraph text.</li>
</ul>
passage: TAGS
#transformers #pytorch #mt5 #text2text-generation #summarization #mT5 #th #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
# mt5-cpe-kmutt-thai-sentence-sum
This repository contains the finetuned mT5-base model for Thai sentence summarization. The architecture of the model is based on mT5 model and fine-tuned on text-summarization pairs in Thai.  Also, this project is a Senior Project of Computer Engineering Student at King Mongkut’s University of Technology Thonburi.## Usage on SimpleTransformer (Tested on version 0.63.4)

(See the example on <a href="URL Colab</a>)### Score
<ul>
  <li>ROUGE-1: 61.7805</li>
  <li>ROUGE-2: 45.9689</li>
  <li>ROUGE-L: 59.3542</li>
</ul>### Intended uses & limitations
<ul>
  <li>You can use this model for Thai sentence text summarization.</li>
  <li>Not intended to use with paragraph text.</li>
</ul>