Migrate model card from transformers-repo

Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755
Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/iarfmoose/roberta-base-bulgarian-pos/README.md

README.md

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+---
+language: bg
+---
+
+# RoBERTa-base-bulgarian-POS
+
+
+The RoBERTa model was originally introduced in [this paper](https://arxiv.org/abs/1907.11692). This model is a version of [RoBERTa-base-Bulgarian](https://huggingface.co/iarfmoose/roberta-base-bulgarian) fine-tuned for part-of-speech tagging.
+
+## Intended uses
+
+The model can be used to predict part-of-speech tags in Bulgarian text. Since the tokenizer uses byte-pair encoding, each word in the text may be split into more than one token. When predicting POS-tags, the last token from each word can be used. Using the last token was found to slightly outperform predictions based on the first token.
+
+An example of this can be found [here](https://github.com/iarfmoose/bulgarian-nlp/blob/master/models/postagger.py).
+
+## Limitations and bias
+
+The pretraining data is unfiltered text from the internet and may contain all sorts of biases.
+
+## Training data
+
+In addition to the pretraining data used in [RoBERTa-base-Bulgarian]([RoBERTa-base-Bulgarian](https://huggingface.co/iarfmoose/roberta-base-bulgarian)), the model was trained on the UPOS tags from [UD_Bulgarian-BTB](https://github.com/UniversalDependencies/UD_Bulgarian-BTB).
+
+## Training procedure
+
+The model was trained for 5 epochs over the training set. The loss was calculated based on label predictions for the last POS-tag for each word. The model achieves 97% on the test set.