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Created card for spanbert-finetuned-squadv1

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---
language: english
thumbnail:
---
# SpanBERT (spanbert-base-cased) fine-tuned on SQuAD v1.1
[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/) for **Q&A** downstream task.
## Details of SpanBERT
A pre-training method that is designed to better represent and predict spans of text.
[SpanBERT: Improving Pre-training by Representing and Predicting Spans](https://arxiv.org/abs/1907.10529)
## Details of the downstream task (Q&A) - Dataset
[SQuAD 1.1](https://rajpurkar.github.io/SQuAD-explorer/) contains 100,000+ question-answer pairs on 500+ articles.
| Dataset | Split | # samples |
| -------- | ----- | --------- |
| SQuAD1.1 | train | 87.7k |
| SQuAD1.1 | eval | 10.6k |
## Model training
The model was trained on a Tesla P100 GPU and 25GB of RAM.
The script for fine tuning can be found [here](https://github.com/huggingface/transformers/blob/master/examples/run_squad.py)
## Results:
| Metric | # Value |
| ------ | --------- |
| **EM** | **85.49** |
| **F1** | **91.98** |
### Raw metrics:
```json
{
"exact": 85.49668874172185,
"f1": 91.9845699540379,
"total": 10570,
"HasAns_exact": 85.49668874172185,
"HasAns_f1": 91.9845699540379,
"HasAns_total": 10570,
"best_exact": 85.49668874172185,
"best_exact_thresh": 0.0,
"best_f1": 91.9845699540379,
"best_f1_thresh": 0.0
}
```
## Comparison:
| Model | EM | F1 score |
| ----------------------------------------------------------------------------------------- | --------- | --------- |
| [SpanBert official repo](https://github.com/facebookresearch/SpanBERT#pre-trained-models) | - | 92.4\* |
| [spanbert-finetuned-squadv1](https://huggingface.co/mrm8488/spanbert-finetuned-squadv1) | **85.49** | **91.98** |
## Model in action
Fast usage with **pipelines**:
```python
from transformers import pipeline
qa_pipeline = pipeline(
"question-answering",
model="mrm8488/spanbert-finetuned-squadv1",
tokenizer="mrm8488/spanbert-finetuned-squadv1"
)
qa_pipeline({
'context': "Manuel Romero has been working hardly in the repository hugginface/transformers lately",
'question': "Who has been working hard for hugginface/transformers lately?"
})
```
> 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