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
