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DistBERT-squad2-QA
Shobhank-iiitdwd/DistBERT-squad2-QA
DistBERT-squad2-QA is a question answering model from Shobhank-iiitdwd. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as mit.
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…
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At a glance
- Task
- Question Answering
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Dec 29, 2022
- Updated
- Dec 29, 2022
- SHA
- 6b1f37ae
Try a prompt
Datasets
Model card
From the Hugging Face model README
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
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- en
- Created
- Dec 29, 2022
- Updated
- Dec 29, 2022