Bert Base Uncased 2 Finetuned RRamicus

🚀 bert-base-uncased-2-finetuned-RRamicus

This model is a fine - tuned version of [bert - base - uncased](https://huggingface.co/bert - base - uncased) on the None dataset. It provides valuable performance with a loss of 1.4784 on the evaluation set.

🚀 Quick Start

This fine - tuned model can be used for various NLP tasks. You can load it using the Hugging Face Transformers library.

✨ Features

• Fine - tuned from the well - known bert - base - uncased model.
• Achieves a loss of 1.4784 on the evaluation set.

📦 Installation

There is no specific installation step provided in the original document.

💻 Usage Examples

There are no code examples in the original document.

📚 Documentation

Model description

This model is a fine - tuned version of [bert - base - uncased](https://huggingface.co/bert - base - uncased) on the None dataset.

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

🔧 Technical Details

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e - 05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 928
• optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Framework versions

• Transformers 4.18.0
• Pytorch 1.10.0+cu111
• Datasets 2.1.0
• Tokenizers 0.12.1

📄 License

This model is licensed under the Apache 2.0 license.