Update README.md

README.md

@@ -105,10 +105,6 @@ model-index:
       verified: true
 ---
 
-# mT5-multilingual-XLSum
-
-This repository contains the mT5 checkpoint finetuned on the 45 languages of [XL-Sum](https://huggingface.co/datasets/csebuetnlp/xlsum) dataset. For finetuning details and scripts,
-see the [paper](https://aclanthology.org/2021.findings-acl.413/) and the [official repository](https://github.com/csebuetnlp/xl-sum). 
 
 
 ## Using this model in `transformers` (tested on 4.11.0.dev0)
@@ -149,80 +145,3 @@ summary = tokenizer.decode(
 print(summary)
 ```
 
-## Benchmarks
-
-Scores on the XL-Sum test sets are as follows:
-
-Language | ROUGE-1 / ROUGE-2 / ROUGE-L
----------|----------------------------
-Amharic | 20.0485 / 7.4111 / 18.0753
-Arabic | 34.9107 / 14.7937 / 29.1623
-Azerbaijani | 21.4227 / 9.5214 / 19.3331
-Bengali | 29.5653 / 12.1095 / 25.1315
-Burmese | 15.9626 / 5.1477 / 14.1819
-Chinese (Simplified) | 39.4071 / 17.7913 / 33.406
-Chinese (Traditional) | 37.1866 / 17.1432 / 31.6184
-English | 37.601 / 15.1536 / 29.8817
-French | 35.3398 / 16.1739 / 28.2041
-Gujarati | 21.9619 / 7.7417 / 19.86
-Hausa | 39.4375 / 17.6786 / 31.6667
-Hindi | 38.5882 / 16.8802 / 32.0132
-Igbo | 31.6148 / 10.1605 / 24.5309
-Indonesian | 37.0049 / 17.0181 / 30.7561
-Japanese | 48.1544 / 23.8482 / 37.3636
-Kirundi | 31.9907 / 14.3685 / 25.8305
-Korean | 23.6745 / 11.4478 / 22.3619
-Kyrgyz | 18.3751 / 7.9608 / 16.5033
-Marathi | 22.0141 / 9.5439 / 19.9208
-Nepali | 26.6547 / 10.2479 / 24.2847
-Oromo | 18.7025 / 6.1694 / 16.1862
-Pashto | 38.4743 / 15.5475 / 31.9065
-Persian | 36.9425 / 16.1934 / 30.0701
-Pidgin | 37.9574 / 15.1234 / 29.872
-Portuguese | 37.1676 / 15.9022 / 28.5586
-Punjabi | 30.6973 / 12.2058 / 25.515
-Russian | 32.2164 / 13.6386 / 26.1689
-Scottish Gaelic | 29.0231 / 10.9893 / 22.8814
-Serbian (Cyrillic) | 23.7841 / 7.9816 / 20.1379
-Serbian (Latin) | 21.6443 / 6.6573 / 18.2336
-Sinhala | 27.2901 / 13.3815 / 23.4699
-Somali | 31.5563 / 11.5818 / 24.2232
-Spanish | 31.5071 / 11.8767 / 24.0746
-Swahili | 37.6673 / 17.8534 / 30.9146
-Tamil | 24.3326 / 11.0553 / 22.0741
-Telugu | 19.8571 / 7.0337 / 17.6101
-Thai | 37.3951 / 17.275 / 28.8796
-Tigrinya | 25.321 / 8.0157 / 21.1729
-Turkish | 32.9304 / 15.5709 / 29.2622
-Ukrainian | 23.9908 / 10.1431 / 20.9199
-Urdu | 39.5579 / 18.3733 / 32.8442
-Uzbek | 16.8281 / 6.3406 / 15.4055
-Vietnamese | 32.8826 / 16.2247 / 26.0844
-Welsh | 32.6599 / 11.596 / 26.1164
-Yoruba | 31.6595 / 11.6599 / 25.0898
-
-
-
-## Citation
-
-If you use this model, please cite the following paper:
-```
-@inproceedings{hasan-etal-2021-xl,
-    title = "{XL}-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages",
-    author = "Hasan, Tahmid  and
-      Bhattacharjee, Abhik  and
-      Islam, Md. Saiful  and
-      Mubasshir, Kazi  and
-      Li, Yuan-Fang  and
-      Kang, Yong-Bin  and
-      Rahman, M. Sohel  and
-      Shahriyar, Rifat",
-    booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
-    month = aug,
-    year = "2021",
-    address = "Online",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/2021.findings-acl.413",
-    pages = "4693--4703",
-}
-```