Create model card (#3654)

* Create model card

* Fix model name in fine-tuning script

model_cards/mrm8488/spanbert-large-finetuned-squadv1/README.md

+---
+language: english
+thumbnail:
+---
+
+# SpanBERT large fine-tuned on SQuAD v1
+
+[SpanBERT](https://github.com/facebookresearch/SpanBERT) created by [Facebook Research](https://github.com/facebookresearch) and fine-tuned on [SQuAD 1.1](https://rajpurkar.github.io/SQuAD-explorer/explore/1.1/dev/) for **Q&A** downstream task ([by them](https://github.com/facebookresearch/SpanBERT#finetuned-models-squad-1120-relation-extraction-coreference-resolution)).
+
+## Details of SpanBERT
+
+[SpanBERT: Improving Pre-training by Representing and Predicting Spans](https://arxiv.org/abs/1907.10529)
+
+## Details of the downstream task (Q&A) - Dataset 📚 🧐 ❓
+
+[SQuAD1.1](https://rajpurkar.github.io/SQuAD-explorer/)
+
+## Model fine-tuning 🏋️‍
+
+You can get the fine-tuning script [here](https://github.com/facebookresearch/SpanBERT)
+
+```bash
+python code/run_squad.py \
+  --do_train \
+  --do_eval \
+  --model spanbert-large-cased \
+  --train_file train-v1.1.json \
+  --dev_file dev-v1.1.json \
+  --train_batch_size 32 \
+  --eval_batch_size 32  \
+  --learning_rate 2e-5 \
+  --num_train_epochs 4 \
+  --max_seq_length 512 \
+  --doc_stride 128 \
+  --eval_metric f1 \
+  --output_dir squad_output \
+  --fp16
+```
+
+## Results Comparison 📝
+
+|                   | SQuAD 1.1     | SQuAD 2.0  | Coref   | TACRED |
+| ----------------------  | ------------- | ---------  | ------- | ------ |
+|                         | F1            | F1         | avg. F1 |  F1    |
+| BERT (base)             | 88.5*         | 76.5*      | 73.1    |  67.7  |
+| SpanBERT (base)         | [92.4*](https://huggingface.co/mrm8488/spanbert-base-finetuned-squadv1)         | [83.6*](https://huggingface.co/mrm8488/spanbert-base-finetuned-squadv2)      | 77.4    |  [68.2](https://huggingface.co/mrm8488/spanbert-base-finetuned-tacred)  |
+| BERT (large)            | 91.3          | 83.3       | 77.1    |  66.4  |
+| SpanBERT (large)        | **94.6** (this)         | [88.7](https://huggingface.co/mrm8488/spanbert-large-finetuned-squadv2)     | 79.6    |  [70.8](https://huggingface.co/mrm8488/spanbert-large-finetuned-tacred)  |
+
+
+Note: The numbers marked as * are evaluated on the development sets becaus those models were not submitted to the official SQuAD leaderboard. All the other numbers are test numbers.
+
+## Model in action
+
+Fast usage with **pipelines**:
+
+```python
+from transformers import pipeline
+
+qa_pipeline = pipeline(
+    "question-answering",
+    model="mrm8488/spanbert-large-finetuned-squadv1",
+    tokenizer="SpanBERT/spanbert-large-cased"
+)
+
+qa_pipeline({
+    'context': "Manuel Romero has been working very hard in the repository hugginface/transformers lately",
+    'question': "How has been working Manuel Romero lately?"
+
+})
+
+# Output: {'answer': 'very hard in the repository hugginface/transformers',
+ 'end': 82,
+ 'score': 0.327230326857725,
+ 'start': 31}
+```
+
+> Created by [Manuel Romero/@mrm8488](https://twitter.com/mrm8488)
+
+> Made with <span style="color: #e25555;">&hearts;</span> in Spain