bert-base-uncased-Masked_Language_Modeling-Reddit_Comments
This model is a fine-tuned version of bert-base-uncased. It achieves the following results on the evaluation set:
- Loss: 2.5415
Model description
This is a masked language modeling project.
For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Masked%20Language%20Model/Datasets%20for%20NLP%20-%20Reddit%20Comments/Datasets_for_NLP_MLM.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/toygarr/datasets-for-natural-language-processing
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 |
---|---|---|---|
2.8757 | 1.0 | 10812 | 2.6382 |
2.6818 | 2.0 | 21624 | 2.5699 |
2.6103 | 3.0 | 32436 | 2.5402 |
Perplexity: 12.70
Framework versions
- Transformers 4.27.0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2