readme: ## ELECTRA_large_discriminator language model fine-tuned on SQuAD2.0
  
  ### with the following results:
  
  ```
    "exact": 87.09677419354838,
    "f1": 89.98343832723452,
    "total": 11873,
    "HasAns_exact": 84.66599190283401,
    "HasAns_f1": 90.44759839056285,
    "HasAns_total": 5928,
    "NoAns_exact": 89.52060555088309,
    "NoAns_f1": 89.52060555088309,
    "NoAns_total": 5945,
    "best_exact": 87.09677419354838,
    "best_exact_thresh": 0.0,
    "best_f1": 89.98343832723432,
    "best_f1_thresh": 0.0
  ```
  ### from script:
  ```
  python ${EXAMPLES}/run_squad.py \
    --model_type electra \
    --model_name_or_path google/electra-large-discriminator \
    --do_train \
    --do_eval \
    --train_file ${SQUAD}/train-v2.0.json \
    --predict_file ${SQUAD}/dev-v2.0.json \
    --version_2_with_negative \
    --do_lower_case \
    --num_train_epochs 3 \
    --warmup_steps 306 \
    --weight_decay 0.01 \
    --learning_rate 3e-5 \
    --max_grad_norm 0.5 \
    --adam_epsilon 1e-6 \
    --max_seq_length 512 \
    --doc_stride 128 \
    --per_gpu_train_batch_size 8 \
    --gradient_accumulation_steps 16 \
    --per_gpu_eval_batch_size 128 \
    --fp16 \
    --fp16_opt_level O1 \
    --threads 12 \
    --logging_steps 50 \
    --save_steps 1000 \
    --overwrite_output_dir \
    --output_dir ${MODEL_PATH}
  ```
  ### using the following system & software:
  ```
  Transformers: 2.11.0
  PyTorch: 1.5.0
  TensorFlow: 2.2.0
  Python: 3.8.1
  OS/Platform: Linux-5.3.0-59-generic-x86_64-with-glibc2.10
  CPU/GPU: Intel i9-9900K / NVIDIA Titan RTX 24GB
  ```
  