readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-base-uncased-pretrain-finetuned-coqa-falttened
    results: []
  ---
  
  <!-- 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-pretrain-finetuned-coqa-falttened
  
  This model is a fine-tuned version of [alistvt/bert-base-uncased-pretrained-mlm-coqa-stories](https://huggingface.co/alistvt/bert-base-uncased-pretrained-mlm-coqa-stories) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.8655
  
  ## 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: 5e-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 |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 3.2886        | 0.29  | 2000  | 3.0142          |
  | 3.0801        | 0.59  | 4000  | 2.8347          |
  | 2.9744        | 0.88  | 6000  | 2.7643          |
  | 2.494         | 1.18  | 8000  | 2.7605          |
  | 2.4417        | 1.47  | 10000 | 2.7790          |
  | 2.4042        | 1.77  | 12000 | 2.7382          |
  | 2.1285        | 2.06  | 14000 | 2.8588          |
  | 2.0569        | 2.36  | 16000 | 2.8937          |
  | 2.0794        | 2.65  | 18000 | 2.8511          |
  | 2.0679        | 2.95  | 20000 | 2.8655          |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.17.0
  - Tokenizers 0.10.3
  