readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: DSPFirst-Finetuning-1
    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. -->
  
  # DSPFirst-Finetuning-1
  
  This model is a fine-tuned version of [ahotrod/electra_large_discriminator_squad2_512](https://huggingface.co/ahotrod/electra_large_discriminator_squad2_512) on a generated Questions and Answers dataset from the DSPFirst textbook based on the SQuAD 2.0 format.
  
  # Dataset
  A visualization of the dataset can be found [here](https://github.gatech.edu/pages/VIP-ITS/textbook_SQuAD_explore/explore/textbookv1.0/textbook/). The split between train and test is 80% and 20% respectively.
  ```
  DatasetDict({
      train: Dataset({
          features: ['id', 'title', 'context', 'question', 'answers'],
          num_rows: 4755
      })
      test: Dataset({
          features: ['id', 'title', 'context', 'question', 'answers'],
          num_rows: 1189
      })
  })
  ```
  
  It achieves the following results on the evaluation set:
  - Loss: 0.9236
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  Since the dataset is generated from the DSPFirst textbook, its quality is not guaranteed.
  
  ## 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: 6
  - eval_batch_size: 6
  - seed: 42
  - gradient_accumulation_steps: 86
  - total_train_batch_size: 516
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Model hyperparameters
  - hidden_dropout_prob: 0.5
  - attention_probs_dropout_prob = 0.5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 6.0131        | 0.7   | 20   | 0.9549          |
  | 6.1542        | 1.42  | 40   | 0.9302          |
  | 6.1472        | 2.14  | 60   | 0.9249          |
  | 5.9662        | 2.84  | 80   | 0.9248          |
  | 6.1467        | 3.56  | 100  | 0.9236          |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  