Edit model card
YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/model-cards#model-card-metadata)

This model is Distilbert base uncased trained on SQuAD v2 as:

export SQUAD_DIR=../../squad2
python3 run_squad.py 
    --model_type distilbert 
    --model_name_or_path distilbert-base-uncased
    --do_train 
    --do_eval 
    --overwrite_cache 
    --do_lower_case 
    --version_2_with_negative 
    --save_steps 100000 
    --train_file $SQUAD_DIR/train-v2.0.json 
    --predict_file $SQUAD_DIR/dev-v2.0.json 
    --per_gpu_train_batch_size 8 
    --num_train_epochs 3 
    --learning_rate 3e-5 
    --max_seq_length 384 
    --doc_stride 128 
    --output_dir ./tmp/distilbert_fine_tuned/

Performance on a dev subset is close to the original paper:

Results: 
{
    'exact': 64.88976637051661, 
    'f1': 68.1776176526635, 
    'total': 6078, 
    'HasAns_exact': 69.7594501718213, 
    'HasAns_f1': 76.62665295288285, 
    'HasAns_total': 2910, 
    'NoAns_exact': 60.416666666666664, 
    'NoAns_f1': 60.416666666666664, 
    'NoAns_total': 3168, 
    'best_exact': 64.88976637051661, 
    'best_exact_thresh': 0.0, 
    'best_f1': 68.17761765266337, 
    'best_f1_thresh': 0.0
}

We are hopeful this might save you time, energy, and compute. Cheers!

Downloads last month
901
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.