|
--- |
|
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 |
|
|
