huggingface-course/bert-finetuned-ner

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test-bert-finetuned-ner

This model is a fine-tuned version of 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

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
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: 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