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README.md

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+# Finetuend `bert-base-multilignual-cased` model on Thai sequence and token classification datasets
+
+<br>
+
+Finetuned XLM Roberta BASE model on Thai sequence and token classification datasets
+The script and documentation can be found at [this repository](https://github.com/vistec-AI/thai2transformers).
+
+<br>
+
+## Model description
+
+<br>
+
+We use the pretrained cross-lingual BERT model (mBERT) as proposed by [[Devlin et al., 2018]](https://arxiv.org/abs/1810.04805). We download the pretrained PyTorch model via HuggingFace's Model Hub (https://huggingface.co/bert-base-multilignual-cased)
+<br>
+
+
+
+## Intended uses & limitations
+
+<br>
+
+You can use the finetuned models for multiclass/multilabel text classification and token classification task.
+
+<br>
+
+**Multiclass text classification**
+
+
+-  `wisesight_sentiment` 
+     
+   4-class text classification task (`positive`, `neutral`, `negative`, and `question`) based on social media posts and tweets.
+
+-  `wongnai_reivews` 
+
+     Users' review rating classification task (scale is ranging from 1 to 5)
+
+-  `generated_reviews_enth` : (`review_star` as label)
+
+     Generated users' review rating classification task (scale is ranging from 1 to 5).
+
+**Multilabel text classification**
+
+-  `prachathai67k`
+
+    Thai topic classification with 12 labels based on news article corpus from prachathai.com. The detail is described in this [page](https://huggingface.co/datasets/prachathai67k).
+    
+
+**Token classification**
+
+-  `thainer` 
+
+    Named-entity recognition tagging with 13 named-entities as descibed in this [page](https://huggingface.co/datasets/thainer).
+
+-  `lst20` : NER NER and POS tagging
+ 
+     Named-entity recognition tagging with 10 named-entities and Part-of-Speech tagging with 16 tags as descibed in this [page](https://huggingface.co/datasets/lst20).
+
+<br>
+
+## How to use
+
+<br>
+
+The example notebook demonstrating how to use finetuned model for inference can be found at this [Colab notebook](https://colab.research.google.com/drive/1Kbk6sBspZLwcnOE61adAQo30xxqOQ9ko)
+
+<br>
+
+
+**BibTeX entry and citation info**
+
+```
+@misc{lowphansirikul2021wangchanberta,
+      title={WangchanBERTa: Pretraining transformer-based Thai Language Models}, 
+      author={Lalita Lowphansirikul and Charin Polpanumas and Nawat Jantrakulchai and Sarana Nutanong},
+      year={2021},
+      eprint={2101.09635},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```