readme: ---
  --license: mit
  tags:
  - generated_from_trainer
  datasets:
  - squad_v2
  model-index:
  - name: roberta-base-finetuned-squad2-lwt
  ---
  
  <!-- 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. -->
  
  ## Model description
  
  #### Finetuned on SQUAD2.0 Dataset
  #### F1: 83.738696142672
  
  Trained on single V100 GPU
  
  Everyone is welcome to use~ 
  
  Hope you have a nice day
  
  
  ## Performance
  
   - HasAns_exact': 77.1255060728745, 'HasAns_f1': 83.87812741260885, 'HasAns_total': 5928,
   - 'NoAns_exact': 83.59966358284272, 'NoAns_f1': 83.59966358284272, 'NoAns_total': 5945,
   - 'best_exact': 80.36721974227238, 'best_exact_thresh': 0.0, 
   - 'best_f1': 83.7386961426719, 'best_f1_thresh': 0.0,
   
   - 'exact': 80.36721974227238, 
   - 'f1': 83.738696142672, 
   - 'total': 11873
  
  # roberta-base-finetuned-squad2-lwt
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the squad_v2 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9441
  
  
  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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 0.871         | 1.0   | 8239  | 0.8156          |
  | 0.6787        | 2.0   | 16478 | 0.8494          |
  | 0.4867        | 3.0   | 24717 | 0.9441          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  
  
  