readme: ---
  language: en
  datasets:
  - squad
  widget:
  - text: "Which name is also used to describe the Amazon rainforest in English?"
    context: "The Amazon rainforest (Portuguese: Floresta Amazônica or Amazônia; Spanish: Selva Amazónica, Amazonía or usually Amazonia; French: Forêt amazonienne; Dutch: Amazoneregenwoud), also known in English as Amazonia or the Amazon Jungle, is a moist broadleaf forest that covers most of the Amazon basin of South America. This basin encompasses 7,000,000 square kilometres (2,700,000 sq mi), of which 5,500,000 square kilometres (2,100,000 sq mi) are covered by the rainforest. This region includes territory belonging to nine nations. The majority of the forest is contained within Brazil, with 60% of the rainforest, followed by Peru with 13%, Colombia with 10%, and with minor amounts in Venezuela, Ecuador, Bolivia, Guyana, Suriname and French Guiana. States or departments in four nations contain \"Amazonas\" in their names. The Amazon represents over half of the planet's remaining rainforests, and comprises the largest and most biodiverse tract of tropical rainforest in the world, with an estimated 390 billion individual trees divided into 16,000 species."
  - text: "How many square kilometers of rainforest is covered in the basin?"
    context: "The Amazon rainforest (Portuguese: Floresta Amazônica or Amazônia; Spanish: Selva Amazónica, Amazonía or usually Amazonia; French: Forêt amazonienne; Dutch: Amazoneregenwoud), also known in English as Amazonia or the Amazon Jungle, is a moist broadleaf forest that covers most of the Amazon basin of South America. This basin encompasses 7,000,000 square kilometres (2,700,000 sq mi), of which 5,500,000 square kilometres (2,100,000 sq mi) are covered by the rainforest. This region includes territory belonging to nine nations. The majority of the forest is contained within Brazil, with 60% of the rainforest, followed by Peru with 13%, Colombia with 10%, and with minor amounts in Venezuela, Ecuador, Bolivia, Guyana, Suriname and French Guiana. States or departments in four nations contain \"Amazonas\" in their names. The Amazon represents over half of the planet's remaining rainforests, and comprises the largest and most biodiverse tract of tropical rainforest in the world, with an estimated 390 billion individual trees divided into 16,000 species."
  license: apache-2.0
  ---
  
  # DistilBERT base uncased distilled SQuAD
  
  ## Table of Contents
  - [Model Details](#model-details)
  - [How To Get Started With the Model](#how-to-get-started-with-the-model)
  - [Uses](#uses)
  - [Risks, Limitations and Biases](#risks-limitations-and-biases)
  - [Training](#training)
  - [Evaluation](#evaluation)
  - [Environmental Impact](#environmental-impact)
  - [Technical Specifications](#technical-specifications)
  - [Citation Information](#citation-information)
  - [Model Card Authors](#model-card-authors)
  
  ## Model Details
  
  **Model Description:** The DistilBERT model was proposed in the blog post [Smaller, faster, cheaper, lighter: Introducing DistilBERT, adistilled version of BERT](https://medium.com/huggingface/distilbert-8cf3380435b5), and the paper [DistilBERT, adistilled version of BERT: smaller, faster, cheaper and lighter](https://arxiv.org/abs/1910.01108). DistilBERT is a small, fast, cheap and light Transformer model trained by distilling BERT base. It has 40% less parameters than *bert-base-uncased*, runs 60% faster while preserving over 95% of BERT's performances as measured on the GLUE language understanding benchmark.
  
  This model is a fine-tune checkpoint of [DistilBERT-base-uncased](https://huggingface.co/distilbert-base-uncased), fine-tuned using (a second step of) knowledge distillation on [SQuAD v1.1](https://huggingface.co/datasets/squad). 
  
  - **Developed by:** Hugging Face
  - **Model Type:** Transformer-based language model
  - **Language(s):** English 
  - **License:** Apache 2.0
  - **Related Models:** [DistilBERT-base-uncased](https://huggingface.co/distilbert-base-uncased)
  - **Resources for more information:**
    - See [this repository](https://github.com/huggingface/transformers/tree/main/examples/research_projects/distillation) for more about Distil\* (a class of compressed models including this model)
    - See [Sanh et al. (2019)](https://arxiv.org/abs/1910.01108) for more information about knowledge distillation and the training procedure
  
  ## How to Get Started with the Model 
  
  Use the code below to get started with the model. 
  
  ```python
  >>> from transformers import pipeline
  >>> question_answerer = pipeline("question-answering", model='distilbert-base-uncased-distilled-squad')
  
  >>> context = r"""
  ... Extractive Question Answering is the task of extracting an answer from a text given a question. An example     of a
  ... question answering dataset is the SQuAD dataset, which is entirely based on that task. If you would like to fine-tune
  ... a model on a SQuAD task, you may leverage the examples/pytorch/question-answering/run_squad.py script.
  ... """
  
  >>> result = question_answe