add deepset/xlm-roberta-large-squad2 model card (#6128)

* Add xlm-r QA model card

* Add tags

model_cards/deepset/xlm-roberta-large-squad2/README.md

+---
+language: multilingual
+tags:
+- question-answering
+datasets:
+- squad_v2
+---
+
+# Multilingual XLM-RoBERTa large for QA on various languages 
+
+## Overview
+**Language model:** xlm-roberta-large  
+**Language:** Multilingual  
+**Downstream-task:** Extractive QA  
+**Training data:** SQuAD 2.0  
+**Eval data:** SQuAD dev set - German MLQA - German XQuAD   
+**Training run:** [MLFlow link](https://public-mlflow.deepset.ai/#/experiments/124/runs/3a540e3f3ecf4dd98eae8fc6d457ff20)  
+**Infrastructure**: 4x Tesla v100
+
+## Hyperparameters
+
+```
+batch_size = 32
+n_epochs = 3
+base_LM_model = "xlm-roberta-large"
+max_seq_len = 256
+learning_rate = 1e-5
+lr_schedule = LinearWarmup
+warmup_proportion = 0.2
+doc_stride=128
+max_query_length=64
+``` 
+
+## Performance
+Evaluated on the SQuAD 2.0 English dev set with the [official eval script](https://worksheets.codalab.org/rest/bundles/0x6b567e1cf2e041ec80d7098f031c5c9e/contents/blob/).
+```
+  "exact": 79.45759285774446,
+  "f1": 83.79259828925511,
+  "total": 11873,
+  "HasAns_exact": 71.96356275303644,
+  "HasAns_f1": 80.6460053117963,
+  "HasAns_total": 5928,
+  "NoAns_exact": 86.93019343986543,
+  "NoAns_f1": 86.93019343986543,
+  "NoAns_total": 5945
+```
+
+Evaluated on German [MLQA: test-context-de-question-de.json](https://github.com/facebookresearch/MLQA)
+```
+"exact": 49.34691166703564,
+"f1": 66.15582561674236,
+"total": 4517,
+```
+
+Evaluated on German [XQuAD: xquad.de.json](https://github.com/deepmind/xquad)
+```
+"exact": 61.51260504201681,
+"f1": 78.80206098332569,
+"total": 1190,
+```
+
+## Usage
+
+### In Transformers
+```python
+from transformers.pipelines import pipeline
+from transformers.modeling_auto import AutoModelForQuestionAnswering
+from transformers.tokenization_auto import AutoTokenizer
+
+model_name = "deepset/xlm-roberta-large-squad2"
+
+# a) Get predictions
+nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+QA_input = {
+    'question': 'Why is model conversion important?',
+    'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
+}
+res = nlp(QA_input)
+
+# b) Load model & tokenizer
+model = AutoModelForQuestionAnswering.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+```
+
+### In FARM
+
+```python
+from farm.modeling.adaptive_model import AdaptiveModel
+from farm.modeling.tokenization import Tokenizer
+from farm.infer import QAInferencer
+
+model_name = "deepset/xlm-roberta-large-squad2"
+
+# a) Get predictions
+nlp = QAInferencer.load(model_name)
+QA_input = [{"questions": ["Why is model conversion important?"],
+             "text": "The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks."}]
+res = nlp.inference_from_dicts(dicts=QA_input, rest_api_schema=True)
+
+# b) Load model & tokenizer
+model = AdaptiveModel.convert_from_transformers(model_name, device="cpu", task_type="question_answering")
+tokenizer = Tokenizer.load(model_name)
+```
+
+### In haystack
+For doing QA at scale (i.e. many docs instead of single paragraph), you can load the model also in [haystack](https://github.com/deepset-ai/haystack/):
+```python
+reader = FARMReader(model_name_or_path="deepset/xlm-roberta-large-squad2")
+# or 
+reader = TransformersReader(model="deepset/xlm-roberta-large-squad2",tokenizer="deepset/xlm-roberta-large-squad2")
+```
+
+
+## Authors
+Branden Chan: `branden.chan [at] deepset.ai`  
+Timo Möller: `timo.moeller [at] deepset.ai`  
+Malte Pietsch: `malte.pietsch [at] deepset.ai`  
+Tanay Soni: `tanay.soni [at] deepset.ai`
+
+## About us
+![deepset logo](https://raw.githubusercontent.com/deepset-ai/FARM/master/docs/img/deepset_logo.png)
+
+We bring NLP to the industry via open source!  
+Our focus: Industry specific language models & large scale QA systems.  
+  
+Some of our work: 
+- [German BERT (aka "bert-base-german-cased")](https://deepset.ai/german-bert)
+- [FARM](https://github.com/deepset-ai/FARM)
+- [Haystack](https://github.com/deepset-ai/haystack/)
+
+Get in touch:
+[Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Website](https://deepset.ai)
+