Model card for albert-base-v2-squad2

model_cards/twmkn9/albert-base-v2-squad2/README.md

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+This model is ALBERT base v2 trained on SQuAD v2 as:
+
+```
+python run_squad.py 
+--model_type albert 
+--model_name_or_path albert-base-v2 
+--do_train --do_eval 
+--do_lower_case 
+--version_2_with_negative 
+--train_file $SQUAD_DIR/train-v2.0.json 
+--predict_file $SQUAD_DIR/dev-v2.0.json 
+--per_gpu_train_batch_size 8 
+--num_train_epochs 3 
+--learning_rate 3e-5 
+--max_seq_length 384 
+--doc_stride 128 
+--output_dir ./tmp/albert_base_fine/
+```
+
+Performance on a dev subset is close to the original paper:
+
+```
+Results: 
+{
+    'exact': 78.71010200723923, 
+    'f1': 81.89228117126069, 
+    'total': 6078, 
+    'HasAns_exact': 75.39518900343643, 
+    'HasAns_f1': 82.04167868004215, 
+    'HasAns_total': 2910, 
+    'NoAns_exact': 81.7550505050505, 
+    'NoAns_f1': 81.7550505050505, 
+    'NoAns_total': 3168, 
+    'best_exact': 78.72655478775913, 
+    'best_exact_thresh': 0.0, 
+    'best_f1': 81.90873395178066, 
+    'best_f1_thresh': 0.0
+}
+```
+
+We are hopeful this might save you time, energy, and compute. Cheers!