Bart Large Finetuned Squad2

🚀 roberta-large-finetuned-squad2

This model is finetuned on SQuAD2.0 for question - answering tasks, based on the facebook/bart - large architecture.

🚀 Quick Start

This model is based on facebook/bart-large and was finetuned on SQuAD2.0. The corresponding papers you can found here (model) and here (data).

✨ Features

• Tags: pytorch, question - answering
• Datasets: squad2
• Metrics: exact, f1

💻 Usage Examples

Basic Usage

from transformers.pipelines import pipeline

model_name = "phiyodr/bart-large-finetuned-squad2"
nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
inputs = {
    'question': 'What discipline did Winkelmann create?',
    'context': 'Johann Joachim Winckelmann was a German art historian and archaeologist. He was a pioneering Hellenist who first articulated the difference between Greek, Greco-Roman and Roman art. "The prophet and founding hero of modern archaeology", Winckelmann was one of the founders of scientific archaeology and first applied the categories of style on a large, systematic basis to the history of art. '
}
nlp(inputs)

🔧 Technical Details

Training procedure

{
    "base_model": "facebook/bart-large",
    "do_lower_case": True,
    "learning_rate": 3e-5,
    "num_train_epochs": 4,
    "max_seq_length": 384,
    "doc_stride": 128,
    "max_query_length": 64,
    "batch_size": 96 
}

Eval results

• Data: dev-v2.0.json
• Script: evaluate-v2.0.py (original script from here)

{
  "exact": 81.96748926134929,
  "f1": 85.93825235371045,
  "total": 11873,
  "HasAns_exact": 78.71120107962213,
  "HasAns_f1": 86.6641144054667,
  "HasAns_total": 5928,
  "NoAns_exact": 85.21446593776282,
  "NoAns_f1": 85.21446593776282,
  "NoAns_total": 5945
}