readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: t5-end2end-questions-generation-cvqualtrics-squad-V1
    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. -->
  
  # t5-end2end-questions-generation-cvqualtrics-squad-V1
  
  ## Model description
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the Custom Domain-Specific dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2337
  
  ### Framework versions
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  
  ## Training procedure
  ### Training hyperparameters
  The following hyperparameters were used during training:
  - learning_rate: 0.0001
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 16
  - total_train_batch_size: 64
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 2.6162        | 0.34  | 100  | 1.8890          |
  | 1.9995        | 0.67  | 200  | 1.6871          |
  | 1.8697        | 1.01  | 300  | 1.6146          |
  | 1.7682        | 1.34  | 400  | 1.5530          |
  | 1.7323        | 1.68  | 500  | 1.5232          |
  | 1.7256        | 2.01  | 600  | 1.4921          |
  | 1.6506        | 2.35  | 700  | 1.4640          |
  | 1.6438        | 2.68  | 800  | 1.4406          |
  | 1.6399        | 3.02  | 900  | 1.4137          |
  | 1.5786        | 3.36  | 1000 | 1.3924          |
  | 1.5805        | 3.69  | 1100 | 1.3788          |
  | 1.5824        | 4.03  | 1200 | 1.3626          |
  | 1.5295        | 4.36  | 1300 | 1.3454          |
  | 1.5333        | 4.7   | 1400 | 1.3356          |
  | 1.537         | 5.03  | 1500 | 1.3230          |
  | 1.5002        | 5.37  | 1600 | 1.3157          |
  | 1.4936        | 5.7   | 1700 | 1.3046          |
  | 1.4937        | 6.04  | 1800 | 1.2958          |
  | 1.4649        | 6.38  | 1900 | 1.2826          |
  | 1.4742        | 6.71  | 2000 | 1.2744          |
  | 1.4641        | 7.05  | 2100 | 1.2603          |
  | 1.4472        | 7.38  | 2200 | 1.2595          |
  | 1.4403        | 7.72  | 2300 | 1.2526          |
  | 1.4508        | 8.05  | 2400 | 1.2475          |
  | 1.4191        | 8.39  | 2500 | 1.2412          |
  | 1.4367        | 8.72  | 2600 | 1.2354          |
  | 1.4272        | 9.06  | 2700 | 1.2386          |
  | 1.4104        | 9.4   | 2800 | 1.2323          |
  | 1.4179        | 9.73  | 2900 | 1.2337          |
  