readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - distilgpt2
  - text-generation
  - english
  model-index:
  - name: distilgpt2-fables-demo
    results: []
  pipeline:
  - text-generation
  widget:
  - text: Once upon a time,
  - text: There was a time when
  - text: Long time ago
  ---
  
  <!-- 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. -->
  
  # distilgpt2-fables-demo
  
  **Training:** The model has been trained using the script provided in the following repository https://github.com/MorenoLaQuatra/transformers-tasks-templates
  
  This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on [demelin/understanding_fables](https://huggingface.co/datasets/demelin/understanding_fables) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.2165
  
  ## Model description
  
  The model is a demo for the fine-tuning of decoder-only models using `transformers` library.
  
  ## Intended uses & limitations
  
  It can be used mainly for prototyping and educational purposes.
  
  ## Training and evaluation data
  
  The [demelin/understanding_fables](https://huggingface.co/datasets/demelin/understanding_fables) dataset has been split into train/test/validation using an 80/10/10 random split (`random_seed = 42`). Google Colab has been used for model fine-tuning.
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | No log        | 1.0   | 38   | 42.4563         |
  | No log        | 2.0   | 76   | 5.2808          |
  | 28.753        | 3.0   | 114  | 3.7712          |
  | 28.753        | 4.0   | 152  | 3.4577          |
  | 28.753        | 5.0   | 190  | 3.3120          |
  | 3.5846        | 6.0   | 228  | 3.2773          |
  | 3.5846        | 7.0   | 266  | 3.2710          |
  | 3.0017        | 8.0   | 304  | 3.2764          |
  | 3.0017        | 9.0   | 342  | 3.2795          |
  | 3.0017        | 10.0  | 380  | 3.3300          |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  