readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - null
  model_index:
  - name: bert-base-uncased-finetuned-QnA
    results:
    - task:
        name: Masked Language Modeling
        type: fill-mask
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # bert-base-uncased-finetuned-QnA
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.0604
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 2e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | No log        | 1.0   | 20   | 3.4894          |
  | No log        | 2.0   | 40   | 3.5654          |
  | No log        | 3.0   | 60   | 3.3185          |
  | No log        | 4.0   | 80   | 3.2859          |
  | No log        | 5.0   | 100  | 3.2947          |
  | No log        | 6.0   | 120  | 3.3998          |
  | No log        | 7.0   | 140  | 3.1642          |
  | No log        | 8.0   | 160  | 3.2653          |
  | No log        | 9.0   | 180  | 3.3427          |
  | No log        | 10.0  | 200  | 3.3549          |
  
  
  ### Framework versions
  
  - Transformers 4.9.1
  - Pytorch 1.9.0+cu102
  - Datasets 1.10.2
  - Tokenizers 0.10.3
  