Bert Finetuned Ner

🚀 test-bert-finetuned-ner

This model is a fine - tuned version of [bert - base - cased](https://huggingface.co/bert - base - cased) on the conll2003 dataset. It can be used for token classification tasks, achieving high precision, recall, F1 - score, and accuracy on the evaluation set, which provides reliable performance for named entity recognition.

🚀 Quick Start

This model is a fine - tuned version of [bert - base - cased](https://huggingface.co/bert - base - cased) on the conll2003 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0600
• Precision: 0.9355
• Recall: 0.9514
• F1: 0.9433
• Accuracy: 0.9868

📚 Documentation

Model description

More information needed

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: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Framework versions

• Transformers 4.11.0.dev0
• Pytorch 1.8.1+cu111
• Datasets 1.12.1.dev0
• Tokenizers 0.10.3

📄 License

This model is licensed under the Apache 2.0 license.