readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: distilbert-base-uncased-scratch-powo_mgh_pt
    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-base-uncased-scratch-powo_mgh_pt
  
  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: 3.0408
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 6.4584        | 0.2   | 200  | 4.7806          |
  | 4.6385        | 0.41  | 400  | 4.3704          |
  | 4.2219        | 0.61  | 600  | 4.0727          |
  | 3.994         | 0.81  | 800  | 3.8772          |
  | 3.8048        | 1.01  | 1000 | 3.6894          |
  | 3.6722        | 1.22  | 1200 | 3.5732          |
  | 3.4828        | 1.42  | 1400 | 3.4203          |
  | 3.3648        | 1.62  | 1600 | 3.3634          |
  | 3.3918        | 1.83  | 1800 | 3.2685          |
  | 3.3919        | 2.03  | 2000 | 3.2027          |
  | 3.1715        | 2.23  | 2200 | 3.1365          |
  | 3.0635        | 2.43  | 2400 | 3.1228          |
  | 3.0804        | 2.64  | 2600 | 3.0595          |
  | 3.0468        | 2.84  | 2800 | 3.0318          |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  