readme: ---
  language: en
  license: cc-by-4.0
  datasets:
  - squad_v2
  model-index:
  - name: deepset/bert-base-uncased-squad2
    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: 75.6529
        name: Exact Match
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTY2YmQ0ZDFjMjRlZWRiZWQ2YWQ4MTM0ODkyYTQ0NmYwMzBlNWViZWQ0ODFhMGJmMmY4ZGYwOTQyMDAyZGNjYyIsInZlcnNpb24iOjF9.UyqonQTsCB0BW86LfPy17kLt3a4r3wMeh04MDam5t_UhElp6N02YpiKOqcb1ethNHjAR0WGyxrcV3TI4d-wFAQ
      - type: f1
        value: 78.6191
        name: F1
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZWRkZWVjMDU2YTcxYWVkZTU1YmUzY2FkNWI5NDJkM2YwMjFmMmE0Njc3MjI5N2Q0NDdhZDNkZWNjMWE5YTRmZiIsInZlcnNpb24iOjF9.ol0Zacd9ZryXazXjgVssGFYG4s5FzbhGGaj1ZEDLVN2ziyzx23bo4GH9PSuGTFxRK2BO5_dxvDupLRqJOF59Bg
  ---
  
  # bert-base-uncased for QA 
  
  ## Overview
  **Language model:** bert-base-uncased  
  **Language:** English  
  **Downstream-task:** Extractive QA  
  **Training data:** SQuAD 2.0  
  **Eval data:** SQuAD 2.0  
  **Infrastructure**: 1x Tesla v100
  
  ## Hyperparameters
  
  ```
  batch_size = 32
  n_epochs = 3
  base_LM_model = "bert-base-uncased"
  max_seq_len = 384
  learning_rate = 3e-5
  lr_schedule = LinearWarmup
  warmup_proportion = 0.2
  doc_stride=128
  max_query_length=64
  ``` 
  
  ## Performance
  ```
  "exact": 73.67977764676156
  "f1": 77.87647139308865
  ```
  
  ## Authors
  - Timo Möller: `timo.moeller [at] deepset.ai`
  - Julian Risch: `julian.risch [at] deepset.ai`
  - Malte Pietsch: `malte.pietsch [at] deepset.ai`
  - Michel Bartels: `michel.bartels [at] deepset.ai`
  ## About us
  ![deepset logo](https://workablehr.s3.amazonaws.com/uploads/account/logo/476306/logo)
  We bring NLP to the industry via open source!  
  Our focus: Industry specific language models & large scale QA systems.  
    
  Some of our work: 
  - [German BERT (aka "bert-base-german-cased")](https://deepset.ai/german-bert)
  - [GermanQuAD and GermanDPR datasets and models (aka "gelectra-base-germanquad", "gbert-base-germandpr")](https://deepset.ai/germanquad)
  - [FARM](https://github.com/deepset-ai/FARM)
  - [Haystack](https://github.com/deepset-ai/haystack/)
  
  Get in touch:
  [Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Discord](https://haystack.deepset.ai/community/join) | [GitHub Discussions](https://github.com/deepset-ai/haystack/discussions) | [Website](https://deepset.ai)
  
  By the way: [we're hiring!](http://www.deepset.ai/jobs)