readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: DistilBERT-POWO_Scratch
    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. -->
  
  # DistilBERT-POWO_Scratch
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 4.9068
  
  ## 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: 5
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 40
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 7.104         | 0.18  | 200  | 5.9641          |
  | 5.6973        | 0.36  | 400  | 5.5992          |
  | 5.5464        | 0.54  | 600  | 5.4564          |
  | 5.377         | 0.72  | 800  | 5.3606          |
  | 5.2162        | 0.9   | 1000 | 5.2674          |
  | 5.1499        | 1.08  | 1200 | 5.2080          |
  | 5.1313        | 1.26  | 1400 | 5.1447          |
  | 5.0138        | 1.44  | 1600 | 5.1041          |
  | 4.9509        | 1.62  | 1800 | 5.0572          |
  | 4.9598        | 1.8   | 2000 | 5.0185          |
  | 4.9581        | 1.98  | 2200 | 5.0109          |
  | 4.8458        | 2.16  | 2400 | 4.9608          |
  | 4.953         | 2.34  | 2600 | 4.9482          |
  | 4.7448        | 2.52  | 2800 | 4.9211          |
  | 4.8574        | 2.71  | 3000 | 4.9093          |
  | 4.8402        | 2.89  | 3200 | 4.8980          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  