Update README.md

README.md

@@ -40,38 +40,53 @@ print("\n" + "-" * 50)
 
 ## Benchmarks
  
-|             |   SC   |  EC   |  DC   |  NER     | NLI      |
-|-------------|--------|-------|-------|----------|----------|
-|`Metrics`      |   `Accuracy` | `F1*`  | `Accuracy` | `F1 (Entity)*`  | `Accuracy` |  
-|[mBERT](https://huggingface.co/bert-base-multilingual-cased)        | 83.39  | 56.02 | 98.64 | 67.40    |  75.40   |
-|[XLM-R](https://huggingface.co/xlm-roberta-base)        | 89.49  | 66.70 | 98.71 | 70.63    |   76.87  |    
-|[sagorsarker/bangla-bert-base](https://huggingface.co/sagorsarker/bangla-bert-base) |  87.30  |  61.51  |  98.79   |  70.97   |   70.48     |
-[monsoon-nlp/bangla-electra](https://huggingface.co/monsoon-nlp/bangla-electra)  |  73.54  | 34.55  | 97.64     | 52.57   |   63.48   |
-|***BanglaBERT***   | **92.18** | **74.27** | **99.07** | **72.18** | **82.94**|
+* Zero-shot cross-lingual transfer-learning
+
+|     Model          |   Params   |     SC (macro-F1)     |      NLI (accuracy)     |    NER  (micro-F1)   |   QA (EM/F1)   |   BangLUE score |
+|----------------|-----------|-----------|-----------|-----------|-----------|-----------|
+|[mBERT](https://huggingface.co/bert-base-multilingual-cased) | 180M  | 27.05 | 62.22 | 39.27 | 59.01/64.18 |  50.35 |
+|[XLM-R (base)](https://huggingface.co/xlm-roberta-base) |  270M   | 42.03 | 72.18 | 45.37 | 55.03/61.83 |  55.29 |
+|[XLM-R (large)](https://huggingface.co/xlm-roberta-large) | 550M  | 68.96 | 78.16 | 57.74 | 71.13/77.70 |  70.74 |
+
+* Supervised fine-tuning
+
+|     Model          |   Params   |     SC (macro-F1)     |      NLI (accuracy)     |    NER  (micro-F1)   |   QA (EM/F1)   |   BangLUE score |
+|----------------|-----------|-----------|-----------|-----------|-----------|-----------|
+|[mBERT](https://huggingface.co/bert-base-multilingual-cased) | 180M  | 67.59 | 75.13 | 68.97 | 67.12/72.64 | 70.29 |
+|[XLM-R (base)](https://huggingface.co/xlm-roberta-base) |  270M   | 69.54 | 78.46 | 73.32 | 68.09/74.27  | 72.82 |        
+|[XLM-R (large)](https://huggingface.co/xlm-roberta-large) | 550M  | 70.97 | 82.40 | 78.39 | 73.15/79.06 | 76.79 |
+|[sahajBERT](https://huggingface.co/neuropark/sahajBERT) | 18M | 71.12 | 76.92 | 70.94 | 65.48/70.69 | 71.03 |
+|[BanglaBERT](https://huggingface.co/csebuetnlp/banglabert) | 110M | 72.89 | 82.80 | 77.78 | 72.63/79.34 | **77.09** |
 
-`*` - Weighted Average
 
-The benchmarking datasets are as follows:
-* **SC:** **[Sentiment Classification](https://ieeexplore.ieee.org/document/8554396/)**
-* **EC:** **[Emotion Classification](https://aclanthology.org/2021.naacl-srw.19/)**
-* **DC:** **[Document Classification](https://arxiv.org/abs/2005.00085)**
-* **NER:** **[Named Entity Recognition](https://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs179349)**
-* **NLI:** **[Natural Language Inference](#datasets)**
 
 
+The benchmarking datasets are as follows:
+* **SC:** **[Sentiment Classification](https://aclanthology.org/2021.findings-emnlp.278)**
+* **NER:** **[Named Entity Recognition](https://multiconer.github.io/competition)**
+* **NLI:** **[Natural Language Inference](https://github.com/csebuetnlp/banglabert/#datasets)**
+* **QA:** **[Question Answering](https://github.com/csebuetnlp/banglabert/#datasets)**
+
 ## Citation
 
 If you use this model, please cite the following paper:
 ```
-@article{bhattacharjee2021banglabert,
-  author    = {Abhik Bhattacharjee and Tahmid Hasan and Kazi Samin and Md Saiful Islam and M. Sohel Rahman and Anindya Iqbal and Rifat Shahriyar},
-  title     = {BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding},
-  journal   = {CoRR},
-  volume    = {abs/2101.00204},
-  year      = {2021},
-  url       = {https://arxiv.org/abs/2101.00204},
-  eprinttype = {arXiv},
-  eprint    = {2101.00204}
+@inproceedings{bhattacharjee-etal-2022-banglabert,
+    title     = {BanglaBERT: Lagnuage Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla},
+    author = "Bhattacharjee, Abhik  and
+      Hasan, Tahmid  and
+      Mubasshir, Kazi  and
+      Islam, Md. Saiful  and
+      Uddin, Wasi Ahmad  and
+      Iqbal, Anindya  and
+      Rahman, M. Sohel  and
+      Shahriyar, Rifat",
+      booktitle = "Findings of the North American Chapter of the Association for Computational Linguistics: NAACL 2022",
+      month = july,
+    year      = {2022},
+    url       = {https://arxiv.org/abs/2101.00204},
+    eprinttype = {arXiv},
+    eprint    = {2101.00204}
 }
 ```