BERT-base MCQ Answer Selection
Fine-tuned BERT-base-uncased to select the correct answer option (AโE) for multiple-choice questions.
Files
model.safetensorsโ fine-tuned weightsconfig.jsonโ model configurationtokenizer.json/tokenizer_config.jsonโ 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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Base model
google-bert/bert-base-uncased