README updated

README.md~

@@ -1,41 +0,0 @@
----
-language: eu
-license: cc-by-4.0
-tags:
-- basque
-- roberta
----
-
-# Roberta-eus Euscrawl base cased
-
-This is a RoBERTa model for Basque model presented in [Does corpus quality really matter for low-resource languages?](https://arxiv.org/abs/2203.08111). There are several models for Basque using the RoBERTa architecture, which are pre-trained using different corpora:
-
-- roberta-eus-euscrawl-base-cased: Basque RoBERTa trained on Euscrawl, a corpus created using tailored crawling from Basque sites, and which is distributed under a CC-BY license. EusCrawl It contains 12,528k documents and 423M tokens.
-- roberta-eus-euscrawl-large-cased: Basque RoBERTa large trained on EusCrawl.
-- roberta-eus-mC4-base-cased: Basque RoBERTa trained on the Basque portion of mc4 dataset.
-- roberta-eus-CC100-base-cased: Basque RoBERTa trained on  Basque portion of cc100 dataset.
-
-The models have been tested on five different downstream tasks for Basque: Topic classification, Sentiment analysis, Stance detection, Named Entity Recognition (NER), and Question Answering (refer to the [paper](https://arxiv.org/abs/2203.08111) for more details). See summary of results below:
-
-
-| Model                            | Topic class. | Sentiment | Stance det. |     NER  |     QA   | Average  |
-|----------------------------------|--------------|-----------|-------------|----------|----------|----------|
-| roberta-eus-euscrawl-base-cased  |         76.2 |      77.7 |        57.4 |    86.8  |    34.6  |    66.5  |
-| roberta-eus-euscrawl-large-cased |     **77.6** |      78.8 |        62.9 | **87.2** | **38.3** | **69.0** |
-| roberta-eus-mC4-base-cased       |         75.3 |  **80.4** |        59.1 |    86.0  |    35.2  |    67.2  |
-| roberta-eus-CC100-base-cased     |         76.2 |      78.8 |    **63.4** |    85.2  |    35.8  |    67.9  |
-
-
-If you use any of these models, please cite the following paper:
-
-```
-@misc{artetxe2022euscrawl,
- title={Does corpus quality really matter for low-resource languages?},
- author={Mikel Artetxe, Itziar Aldabe, Rodrigo Agerri,
-         Olatz Perez-de-Viñaspre, Aitor Soroa},
- year={2022},
- eprint={2203.08111},
- archivePrefix={arXiv},
- primaryClass={cs.CL}
-}
-```