transformers tensorboard safetensors distilbert question-answering squad fine-tuning en dataset:squad base_model:distilbert/distilbert-base-uncased base_model:finetune:distilbert/distilbert-base-uncased license:mit model-index endpoints_compatible region:us
---
base_model: distilbert-base-uncased
datasets:
- squad
language:
- en
library_name: transformers
license: mit
tags:
- question-answering
- distilbert
- squad
- fine-tuning
model-index:
- name: my_awesome_qa_model
  results:
  - task:
      type: question-answering
      name: Question Answering
    dataset:
      name: SQuAD v1.1
      type: squad
      split: validation
    metrics:
    - type: exact_match
      value: Please fill in your EM score
      name: Exact Match
    - type: f1
      value: Please fill in your F1 score
      name: F1 Score
---

# my_awesome_qa_model

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased), trained on the [SQuAD v1.1 dataset](https://huggingface.co/datasets/squad).

It achieved the following results on the validation set:

- **Loss**: 1.7489

## How to Use

```python
from transformers import pipeline

# Load the model
question_answerer = pipeline(
    "question-answering",
    model="real-jiakai/my_awesome_qa_model",
    tokenizer="real-jiakai/my_awesome_qa_model"
)

# English example
context_en = """
Donald Trump was the 45th president of the United States, serving from 2017 to 2021.
"""

question_en = "Who was the 45th president of the United States?"

result_en = question_answerer(question=question_en, context=context_en)
print("Answer:", result_en['answer'])
```

## License

This model is licensed under the [MIT](https://opensource.org/license/mit) License.

## Citation

If you use this model in your work, please cite:

```
@misc{my_awesome_qa_model,
  author       = {real-jiakai},
  title        = {my_awesome_qa_model},
  year         = {2024},
  url          = {https://huggingface.co/real-jiakai/my_awesome_qa_model},
  publisher    = {Hugging Face}
}
```