Bert Base Uncased

🚀 bert-base-uncased

This bert-base-uncased model is trained on a GitHub issue dataset. It offers valuable insights and performance in relevant tasks, achieving a loss of 1.2437 on the evaluation set.

🚀 Quick Start

This model was trained on a dataset of issues from github. It achieves the following results on the evaluation set:

• Loss: 1.2437

📚 Documentation

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

Masked language model trained on github issue data with token length of 128.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 16

Training results

Framework versions

• Transformers 4.14.1
• Pytorch 1.9.0
• Datasets 1.11.0
• Tokenizers 0.10.3

📄 License

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🔧 Technical Details

No specific technical details (more than 50 - word description) provided in the original document, so this section is skipped.

💻 Usage Examples

No code examples provided in the original document, so this section is skipped.

📦 Installation

No installation steps provided in the original document, so this section is skipped.

✨ Features

No feature descriptions provided in the original document, so this section is skipped.