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