readme: ---
  language: en
  license: mit
  tags:
  - exbert
  datasets:
  - squad_v2
  thumbnail: https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/format/webp/germanquad.jpg
  model-index:
  - name: Shobhank-iiitdwd/DistBERT-squad2-QA-768d
    results:
    - task:
        type: question-answering
        name: Question Answering
      dataset:
        name: squad_v2
        type: squad_v2
        config: squad_v2
        split: validation
      metrics:
      - type: exact_match
        value: 73.8248
        name: Exact Match
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMGFmZmFiN2E5ODZkOTkyMjQ1NTUzMmQwMjc0M2RlYzVlNmM4YTFlNzA4YzIwY2JkY2EyNDg2ZTY3OTdjZTVlZiIsInZlcnNpb24iOjF9.ZZ6c2OI3lzeNhuSWTh28j00zk-sPrqkTvdVBZv2wJc1D4YnR-xOj72haybT6MV_xeYqTg3-x9L8PsWSS20NaDw
      - type: f1
        value: 77.1684
        name: F1
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzAxMDk1YzI5ZjA2N2ZmMzAxNjgxYzJiNzAzYmI1ZWU5ZDRmYWY3OWJmMjlmNDcyMGE0YWY5NjNhZTk4YWY5ZSIsInZlcnNpb24iOjF9.rF3raNGUSYv5D2xzWLZztD99vwDKvWb22LG32RomrDGP6XKTbCVqZzAw5UFw93jKb0VoLApbQQ-AOGxLj3U_Cg
  ---
  
  ## 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
  ```
  