gpt2-Causal_Language_Model-AG_News

This model is a fine-tuned version of gpt2. It achieves the following results on the evaluation set:

• Loss: 3.1318

Model description

This is a causal language 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/AG%20News/GPT2%20Version/GPT2%20-%20AG_News_CLM.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/thedevastator/new-dataset-for-text-classification-ag-news

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
3.4865	1.0	6099	3.2184
3.2388	2.0	12198	3.1502
3.161	3.0	18297	3.1318

Perplexity: 22.92

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.10.1
• Tokenizers 0.13.2