Update README.md
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### with the following results:
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### with the following results:
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```
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```
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"exact": 84.02257222269014,
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"exact": 84.46896319380106,
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"f1": 87.47063479332766,
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"f1": 87.85388093408943,
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"total": 11873,
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"total": 11873,
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"HasAns_exact": 81.19095816464238,
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"HasAns_exact": 81.37651821862349,
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"HasAns_f1": 88.0969714745582,
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"HasAns_f1": 88.1560607844881,
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"HasAns_total": 5928,
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"HasAns_total": 5928,
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"NoAns_exact": 86.84608915054667,
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"NoAns_exact": 87.55256518082422,
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"NoAns_f1": 86.84608915054667,
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"NoAns_f1": 87.55256518082422,
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"NoAns_total": 5945,
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"NoAns_total": 5945,
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"best_exact": 84.02257222269014,
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"best_exact": 84.46896319380106,
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"best_exact_thresh": 0.0,
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"best_exact_thresh": 0.0,
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"best_f1": 87.47063479332759,
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"best_f1": 87.85388093408929,
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"best_f1_thresh": 0.0
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"best_f1_thresh": 0.0
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```
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```
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### from script:
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### from script:
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```
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```
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python -m torch.distributed.launch --nproc_per_node=2 ${RUN_SQUAD_DIR}/run_squad.py \
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python ${EXAMPLES}/run_squad.py \
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--model_type roberta \
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--model_type roberta \
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--model_name_or_path roberta-large \
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--model_name_or_path roberta-large \
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--do_train \
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--do_train \
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--train_file ${SQUAD_DIR}/train-v2.0.json \
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--do_eval \
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--predict_file ${SQUAD_DIR}/dev-v2.0.json \
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--train_file ${SQUAD}/train-v2.0.json \
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--predict_file ${SQUAD}/dev-v2.0.json \
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--version_2_with_negative \
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--version_2_with_negative \
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--num_train_epochs 2 \
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--warmup_steps 328 \
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--weight_decay 0.01 \
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--do_lower_case \
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--do_lower_case \
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--learning_rate 1.5e-5 \
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--num_train_epochs 3 \
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--warmup_steps 1642 \
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--weight_decay 0.01 \
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--learning_rate 3e-5 \
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--adam_epsilon 1e-6 \
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--max_seq_length 512 \
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--max_seq_length 512 \
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--doc_stride 128 \
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--doc_stride 128 \
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--save_steps 1000 \
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--per_gpu_train_batch_size 8 \
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--per_gpu_train_batch_size 1 \
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--gradient_accumulation_steps 6 \
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--gradient_accumulation_steps 24 \
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--per_gpu_eval_batch_size 48 \
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--threads 12 \
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--logging_steps 50 \
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--logging_steps 50 \
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--threads 10 \
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--save_steps 2000 \
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--overwrite_cache \
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--overwrite_output_dir \
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--output_dir ${MODEL_PATH}
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python ${RUN_SQUAD_DIR}/run_squad.py \
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--model_type roberta \
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--model_name_or_path ${MODEL_PATH} \
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--do_eval \
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--train_file ${SQUAD_DIR}/train-v2.0.json \
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--predict_file ${SQUAD_DIR}/dev-v2.0.json \
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--version_2_with_negative \
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--do_lower_case \
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--max_seq_length 512 \
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--per_gpu_eval_batch_size 24 \
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--eval_all_checkpoints \
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--overwrite_output_dir \
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--overwrite_output_dir \
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--output_dir ${MODEL_PATH}
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--output_dir ${MODEL_PATH}
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$@
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$@
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```
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```
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### using the following system & software:
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### using the following system & software:
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```
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```
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OS/Platform: Linux-4.15.0-91-generic-x86_64-with-debian-buster-sid
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GPU/CPU: 2 x NVIDIA 1080Ti / Intel i7-8700
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Transformers: 2.7.0
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Transformers: 2.7.0
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PyTorch: 1.4.0
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PyTorch: 1.4.0
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TensorFlow: 2.1.0
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TensorFlow: 2.1.0
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Python: 3.7.7
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Python: 3.7.7
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OS/Platform: Linux-5.3.0-46-generic-x86_64-with-debian-buster-sid
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CPU/GPU: Intel i9-9900K / NVIDIA Titan RTX 24GB
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```
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```
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