[Model card] model card for electra-base QA model (#4936)

model_cards/valhalla/electra-base-discriminator-finetuned_squadv1/README.md

+# ELECTRA-BASE-DISCRIMINATOR finetuned on SQuADv1
+
+This is electra-base-discriminator model finetuned on SQuADv1 dataset for for question answering task.
+
+## Model details
+As mentioned in the original paper: ELECTRA is a new method for self-supervised language representation learning.
+It can be used to pre-train transformer networks using relatively little compute. 
+ELECTRA models are trained to distinguish "real" input tokens vs "fake" input tokens generated by another neural network, 
+similar to the discriminator of a GAN. At small scale, ELECTRA achieves strong results even when trained on a single GPU.
+At large scale, ELECTRA achieves state-of-the-art results on the SQuAD 2.0 dataset.
+
+| Param               | #Value |
+|---------------------|--------|
+| layers              | 12     |
+| hidden size         | 768    |
+| num attetion heads  | 12     |
+| on disk size        | 436MB  |
+
+## Model training
+This model was trained on google colab v100 GPU. 
+You can find the fine-tuning colab here
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/11yo-LaFsgggwmDSy2P8zD3tzf5cCb-DU?usp=sharing).
+
+## Results
+The results are actually slightly better than given in the paper. 
+In the paper the authors mentioned that electra-base achieves 84.5 EM and 90.8 F1
+
+| Metric | #Value |
+|--------|--------|
+| EM     | 85.0520|
+| F1     | 91.6050|
+
+
+## Model in Action  🚀
+```python3
+from transformers import pipeline
+
+nlp = pipeline('question-answering', model='valhalla/electra-base-discriminator-finetuned_squadv1')
+nlp({
+    'question': 'What is the answer to everything ?',
+    'context': '42 is the answer to life the universe and everything'
+})
+=> {'answer': '42', 'end': 2, 'score': 0.981274963050339, 'start': 0}
+```
+
+> Created with ❤️ by Suraj Patil [![Github icon](https://cdn0.iconfinder.com/data/icons/octicons/1024/mark-github-32.png)](https://github.com/patil-suraj/)
+[![Twitter icon](https://cdn0.iconfinder.com/data/icons/shift-logotypes/32/Twitter-32.png)](https://twitter.com/psuraj28)