Electricidad small + Spanish SQuAD v1 ⚡❓
Electricidad-small-discriminator fine-tuned on Spanish SQUAD v1.1 dataset for Q&A downstream task.
Details of the downstream task (Q&A) - Dataset 📚
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:
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 |
{
'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:
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 | LinkedIn
Made with ♥ in Spain
- Downloads last month
- 12
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.