Migrate model card from transformers-repo

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Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/a-ware/xlmroberta-squadv2/README.md

README.md

@@ -0,0 +1,59 @@
+---
+datasets:
+- squad_v2
+---
+
+# XLM-ROBERTA-LARGE finetuned on SQuADv2
+
+This is xlm-roberta-large model finetuned on SQuADv2 dataset for question answering task
+
+## Model details
+XLM-Roberta was propsed in the [paper](https://arxiv.org/pdf/1911.02116.pdf) **XLM-R: State-of-the-art cross-lingual understanding through self-supervision
+
+## Model training
+This model was trained with following parameters using simpletransformers wrapper:
+```
+train_args = {
+    'learning_rate': 1e-5,
+    'max_seq_length': 512,
+    'doc_stride': 512,
+    'overwrite_output_dir': True,
+    'reprocess_input_data': False,
+    'train_batch_size': 8,
+    'num_train_epochs': 2,
+    'gradient_accumulation_steps': 2,
+    'no_cache': True,
+    'use_cached_eval_features': False,
+    'save_model_every_epoch': False,
+    'output_dir': "bart-squadv2",
+    'eval_batch_size': 32,
+    'fp16_opt_level': 'O2',
+    }
+```
+
+## Results
+```{"correct": 6961, "similar": 4359, "incorrect": 553, "eval_loss": -12.177856394381962}```
+
+## Model in Action  🚀
+```python3
+from transformers import XLMRobertaTokenizer, XLMRobertaForQuestionAnswering
+import torch
+
+tokenizer = XLMRobertaTokenizer.from_pretrained('a-ware/xlmroberta-squadv2')
+model = XLMRobertaForQuestionAnswering.from_pretrained('a-ware/xlmroberta-squadv2')
+
+question, text = "Who was Jim Henson?", "Jim Henson was a nice puppet"
+encoding = tokenizer(question, text, return_tensors='pt')
+input_ids = encoding['input_ids']
+attention_mask = encoding['attention_mask']
+
+start_scores, end_scores = model(input_ids, attention_mask=attention_mask, output_attentions=False)[:2]
+
+all_tokens = tokenizer.convert_ids_to_tokens(input_ids[0])
+answer = ' '.join(all_tokens[torch.argmax(start_scores) : torch.argmax(end_scores)+1])
+answer = tokenizer.convert_tokens_to_ids(answer.split())
+answer = tokenizer.decode(answer)
+#answer => 'a nice puppet' 
+```
+
+> Created with ❤️ by A-ware UG [![Github icon](https://cdn0.iconfinder.com/data/icons/octicons/1024/mark-github-32.png)](https://github.com/aware-ai)