named-entity-recognition-distilbert-A

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named-entity-recognition-distilbert-A

This model is a fine-tuned version of distilbert-base-uncased on the Multinerd dataset. It achieves the following results on the evaluation set:

• Loss: 0.0606
• Precision: 0.8940
• Recall: 0.9027
• F1: 0.8983
• Accuracy: 0.9833

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:

• learning_rate: 2e-05
• train_batch_size: 32
• eval_batch_size: 16
• 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 4.35.2
• Pytorch 2.1.1+cu121
• Datasets 2.15.0
• Tokenizers 0.15.0

Citation

Bibtex

@software{Ali_Raza,
    author = {Raza, Ali},
    license = { BSD-2-Clause license},
    title = {{Named Entity Recognition using Multinerd}},
    url = {https://github.com/raza4729/NER}
}