---
license: mit
tags:
- generated_from_trainer
model-index:
- name: distilgpt2-CLM_US_Economic_News_Articles
  results: []
language:
- en
metrics:
- perplexity
---

# distilgpt2-CLM_US_Economic_News_Articles

This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2).
It achieves the following results on the evaluation set:
- Loss: 3.4472

## Model description

This is a causal lamguage modeling project.

For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Causal%20Language%20Modeling/US%20Economic%20News%20Articles/US%20Economic%20News%20Articles%20-%20CLM.ipynb

## Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

## Training and evaluation data

Dataset Source: https://www.kaggle.com/datasets/heeraldedhia/us-economic-news-articles

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.6225        | 1.0   | 1869 | 3.4853          |
| 3.5092        | 2.0   | 3738 | 3.4555          |
| 3.4514        | 3.0   | 5607 | 3.4472          |

Perplexity: 31.41

### Framework versions

- Transformers 4.26.1
- Pytorch 1.12.1
- Datasets 2.9.0
- Tokenizers 0.12.1


## License Notice
This model is a fine-tuned derivative of a pretrained model.
Users must comply with the original model license.


## Dataset Notice
This model was fine-tuned on third-party datasets which may have separate licenses or usage restrictions.