Bert Base Uncased Finetuned Squad V2

🚀 HomayounSadri/bert-base-uncased-finetuned-squad-v2

This model is a fine - tuned variant of [bert - base - uncased](https://huggingface.co/bert - base - uncased) on an unknown dataset. It offers evaluation results such as Train Loss, Validation Loss, and the number of Epochs, providing insights into its performance.

🚀 Quick Start

This section will be updated once the quick - start steps are available.

✨ Features

This model is a fine - tuned version of bert - base - uncased, which may potentially have better performance on specific tasks compared to the base model. It provides evaluation metrics like Train Loss, Validation Loss, and Epoch information.

📚 Documentation

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e - 05, 'decay_steps': 11064, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e - 08, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Framework versions

• Transformers 4.18.0
• TensorFlow 2.8.0
• Datasets 2.1.0
• Tokenizers 0.12.1

📄 License

This model is licensed under the Apache 2.0 license.