Create model card (#5396)

Create model card for electicidad-small (Spanish Electra) fine-tuned on SQUAD-esv1

model_cards/mrm8488/electricidad-small-finetuned-squadv1-es/README.md

+---
+language: spanish
+thumbnail: https://imgur.com/uxAvBfh
+---
+
+# Electricidad small + Spanish SQuAD v1 ⚡❓
+
+[Electricidad-small-discriminator](https://huggingface.co/mrm8488/electricidad-small-discriminator) fine-tuned on [Spanish SQUAD v1.1 dataset](https://github.com/ccasimiro88/TranslateAlignRetrieve/tree/master/SQuAD-es-v1.1) for **Q&A** downstream task.
+
+## Details of the downstream task (Q&A) - Dataset 📚
+
+[SQuAD-es-v1.1](https://github.com/ccasimiro88/TranslateAlignRetrieve/tree/master/SQuAD-es-v1.1)
+
+| Dataset split | # Samples |
+| ------------- | --------- |
+| Train         | 130 K     |
+| Test          | 11 K      |
+
+## Model training 🏋️‍
+
+The model was trained on a Tesla P100 GPU and 25GB of RAM with the following command:
+
+```bash
+python /content/transformers/examples/question-answering/run_squad.py \
+  --model_type electra \
+  --model_name_or_path 'mrm8488/electricidad-small-discriminator' \
+  --do_eval \
+  --do_train \
+  --do_lower_case \
+  --train_file '/content/dataset/train-v1.1-es.json' \
+  --predict_file '/content/dataset/dev-v1.1-es.json' \
+  --per_gpu_train_batch_size 16 \
+  --learning_rate 3e-5 \
+  --num_train_epochs 10 \
+  --max_seq_length 384 \
+  --doc_stride 128 \
+  --output_dir '/content/electricidad-small-finetuned-squadv1-es' \
+  --overwrite_output_dir \
+  --save_steps 1000
+```
+
+## Test set Results 🧾
+
+| Metric | # Value   |
+| ------ | --------- |
+| **EM** | **46.82** |
+| **F1** | **64.79** |
+
+```json
+{
+'exact': 46.82119205298013,
+'f1': 64.79435260021918,
+'total': 10570,
+'HasAns_exact': 46.82119205298013,
+HasAns_f1': 64.79435260021918,
+'HasAns_total': 10570,
+'best_exact': 46.82119205298013,
+'best_exact_thresh': 0.0,
+'best_f1': 64.79435260021918,
+'best_f1_thresh': 0.0
+}
+```
+
+### Model in action 🚀
+
+Fast usage with **pipelines**:
+
+```python
+from transformers import pipeline
+
+qa_pipeline = pipeline(
+    "question-answering",
+    model="mrm8488/electricidad-small-finetuned-squadv1-es",
+    tokenizer="mrm8488/electricidad-small-finetuned-squadv1-es"
+)
+
+context = "Manuel ha creado una versión del modelo Electra small en español que alcanza una puntuación F1 de 65 en el dataset SQUAD-es y sólo pesa 50 MB"
+
+q1 = "Cuál es su marcador F1?"
+q2 = "¿Cuál es el tamaño del modelo?"
+q3 = "¿Quién lo ha creado?"
+q4 = "¿Que es lo que ha hecho Manuel?"
+
+
+questions = [q1, q2, q3, q4]
+
+for question in questions:
+  result = qa_pipeline({
+    'context': context,
+    'question': question})
+  print(result)
+
+# Output:
+{'score': 0.14836778166355025, 'start': 98, 'end': 100, 'answer': '65'}
+{'score': 0.32219420810758237, 'start': 136, 'end': 140, 'answer': '50 MB'}
+{'score': 0.9672326951118713, 'start': 0, 'end': 6, 'answer': 'Manuel'}
+{'score': 0.23552458113848118, 'start': 10, 'end': 53, 'answer': 'creado una versión del modelo Electra small'}
+```
+
+> Created by [Manuel Romero/@mrm8488](https://twitter.com/mrm8488) | [LinkedIn](https://www.linkedin.com/in/manuel-romero-cs/)
+
+> Made with <span style="color: #e25555;">&hearts;</span> in Spain