---
license: apache-2.0
tags:
- generated_from_trainer
- distilgpt2
- text-generation
- english
datasets: demelin/understanding_fables
pipeline:
- text-generation
widget:
- text: Once upon a time,
- text: There was a time when
- text: Long time ago
model-index:
- name: distilgpt2-fables-demo
  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. -->

# 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