| # 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 | |
| --- | |