Create README.md

model_cards/ahotrod/roberta_large_squad2/README.md

+## RoBERTa-large language model fine-tuned on SQuAD2.0
+
+### with the following results:
+
+```
+  "exact": 84.02257222269014,
+  "f1": 87.47063479332766,
+  "total": 11873,
+  "HasAns_exact": 81.19095816464238,
+  "HasAns_f1": 88.0969714745582,
+  "HasAns_total": 5928,
+  "NoAns_exact": 86.84608915054667,
+  "NoAns_f1": 86.84608915054667,
+  "NoAns_total": 5945,
+  "best_exact": 84.02257222269014,
+  "best_exact_thresh": 0.0,
+  "best_f1": 87.47063479332759,
+  "best_f1_thresh": 0.0
+```
+### from script:
+```
+python -m torch.distributed.launch --nproc_per_node=2 ${RUN_SQUAD_DIR}/run_squad.py \
+  --model_type roberta \
+  --model_name_or_path roberta-large \
+  --do_train \
+  --train_file ${SQUAD_DIR}/train-v2.0.json \
+  --predict_file ${SQUAD_DIR}/dev-v2.0.json \
+  --version_2_with_negative \
+  --num_train_epochs 2 \
+  --warmup_steps 328 \
+  --weight_decay 0.01 \
+  --do_lower_case \
+  --learning_rate 1.5e-5 \
+  --max_seq_length 512 \
+  --doc_stride 128 \
+  --save_steps 1000 \
+  --per_gpu_train_batch_size 1 \
+  --gradient_accumulation_steps 24 \
+  --logging_steps 50 \
+  --threads 10 \
+  --overwrite_cache \
+  --overwrite_output_dir \
+  --output_dir ${MODEL_PATH}
+
+python ${RUN_SQUAD_DIR}/run_squad.py \
+  --model_type roberta \
+  --model_name_or_path ${MODEL_PATH} \
+  --do_eval \
+  --train_file ${SQUAD_DIR}/train-v2.0.json \
+  --predict_file ${SQUAD_DIR}/dev-v2.0.json \
+  --version_2_with_negative \
+  --do_lower_case \
+  --max_seq_length 512 \
+  --per_gpu_eval_batch_size 24 \
+  --eval_all_checkpoints \
+  --overwrite_output_dir \
+  --output_dir ${MODEL_PATH}
+$@
+```
+### using the following system & software:
+```
+OS/Platform: Linux-4.15.0-91-generic-x86_64-with-debian-buster-sid
+GPU/CPU: 2 x NVIDIA 1080Ti / Intel i7-8700
+Transformers: 2.7.0
+PyTorch: 1.4.0
+TensorFlow: 2.1.0
+Python: 3.7.7
+```