Bert Finetuned Small Data Uia

🚀 bert-finetuned-small-data-uia

This model is a fine - tuned version of bert-base-uncased on the None dataset, offering potential for relevant natural language processing tasks.

🚀 Quick Start

This section provides a high - level overview of the bert - finetuned - small - data - uia model. It is a fine - tuned variant of the well - known bert - base - uncased model.

📚 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

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0002
• train_batch_size: 4
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
• lr_scheduler_type: linear
• num_epochs: 20
• mixed_precision_training: Native AMP

Training results

More information needed

Framework versions

• Transformers 4.25.1
• Pytorch 1.12.1+cu113
• Datasets 2.7.1
• Tokenizers 0.13.2

📄 License

This model is licensed under the Apache 2.0 license.