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This model is [ALBERT base v2](https://huggingface.co/albert-base-v2) trained on SQuAD v2 as: |
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``` |
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export SQUAD_DIR=../../squad2 |
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python3 run_squad.py |
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--model_type albert |
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--model_name_or_path albert-base-v2 |
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--do_train |
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--do_eval |
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--overwrite_cache |
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--do_lower_case |
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--version_2_with_negative |
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--save_steps 100000 |
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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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--per_gpu_train_batch_size 8 |
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--num_train_epochs 3 |
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--learning_rate 3e-5 |
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--max_seq_length 384 |
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--doc_stride 128 |
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--output_dir ./tmp/albert_fine/ |
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``` |
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Performance on a dev subset is close to the original paper: |
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``` |
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Results: |
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{ |
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'exact': 78.71010200723923, |
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'f1': 81.89228117126069, |
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'total': 6078, |
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'HasAns_exact': 75.39518900343643, |
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'HasAns_f1': 82.04167868004215, |
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'HasAns_total': 2910, |
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'NoAns_exact': 81.7550505050505, |
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'NoAns_f1': 81.7550505050505, |
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'NoAns_total': 3168, |
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'best_exact': 78.72655478775913, |
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'best_exact_thresh': 0.0, |
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'best_f1': 81.90873395178066, |
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'best_f1_thresh': 0.0 |
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} |
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``` |
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We are hopeful this might save you time, energy, and compute. Cheers! |