BERT-base MCQ Answer Selection

Fine-tuned BERT-base-uncased to select the correct answer option (Aโ€“E) for multiple-choice questions.

Files

  • model.safetensors โ€” fine-tuned weights
  • config.json โ€” model configuration
  • tokenizer.json / tokenizer_config.json โ€” tokenizer

Training details

  • Base model: google-bert/bert-base-uncased
  • Task: rank 5 answer options per prompt (top-1 accuracy + mAP@3)
  • Format: prompt + 5 options, each option scored via the [CLS] embedding

Usage

from transformers import AutoModelForSequenceClassification, AutoTokenizer
from safetensors.torch import load_file

# Load tokenizer
tokenizer = AutoTokenizer.from_pretrained("22f3001251/dlgenai-bert-roberta")

See training/bert_roberta.ipynb in the companion repo for the full training and inference flow.

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