Overview
Language model: Shobhank-iiitdwd/DistBERT-squad2-QA
Language: English
Training data: SQuAD 2.0 training set x 20 augmented + SQuAD 2.0 training set without augmentation
Eval data: SQuAD 2.0 dev set
Infrastructure: 1x V100 GPU
Published: Dec 8th, 2021
Details
- haystack's intermediate layer and prediction layer distillation features were used for training. bert-base-uncased-squad2 was used as the teacher model and DBERT_General_6L_768D was used as the student model.
Hyperparameters
Intermediate layer distillation
batch_size = 26
n_epochs = 5
max_seq_len = 384
learning_rate = 5e-5
lr_schedule = LinearWarmup
embeds_dropout_prob = 0.1
temperature = 1
Prediction layer distillation
batch_size = 26
n_epochs = 5
max_seq_len = 384
learning_rate = 3e-5
lr_schedule = LinearWarmup
embeds_dropout_prob = 0.1
temperature = 1
distillation_loss_weight = 1.0
Performance
"exact": 71.87736882001179
"f1": 76.36111895973675
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Dataset used to train Shobhank-iiitdwd/DistBERT-squad2-QA
Evaluation results
- Exact Match on squad_v2validation set self-reported73.825
- F1 on squad_v2validation set self-reported77.168