readme: # DistilBERT--SQuAD-v1
  
  Training is done on the [SQuAD](https://huggingface.co/datasets/squad) dataset. The model can be accessed via [HuggingFace](https://huggingface.co/abhilash1910/distilbert-squadv1):
  
  
  ## Model Specifications
  
  We have used the following parameters:
  
  - Training Batch Size : 512
  - Learning Rate : 3e-5
  - Training Epochs : 0.75
  - Sequence Length : 384
  - Stride : 128
  
  
  ## Usage Specifications
  
  
  ```python
  
  from transformers import AutoModelForQuestionAnswering,AutoTokenizer,pipeline
  model=AutoModelForQuestionAnswering.from_pretrained('abhilash1910/distilbert-squadv1')
  tokenizer=AutoTokenizer.from_pretrained('abhilash1910/distilbert-squadv1')
  nlp_QA=pipeline('question-answering',model=model,tokenizer=tokenizer)
  QA_inp={
      'question': 'What is the fund price of Huggingface in NYSE?',
      'context': 'Huggingface Co. has a total fund price of $19.6 million dollars'
  }
  result=nlp_QA(QA_inp)
  result
  ```
  
  The result is:
  
  ```bash
  
  {'score': 0.38547369837760925,
   'start': 42,
   'end': 55,
   'answer': '$19.6 million'}
   ```
  
  ---
  language:
  - en
  license: apache-2.0
  datasets:
  - squad_v1
  
  ---
  
  