importsmart/bert-to-distilbert-NER

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bert-to-distilbert-NER

This model is a fine-tuned version of dslim/bert-base-NER on the conll2003 dataset. It achieves the following results on the evaluation set:

• —Loss: 44.0386
• —Precision: 0.0145
• —Recall: 0.0185
• —F1: 0.0163
• —Accuracy: 0.7597

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: 6e-05
• —trainbatchsize: 128
• —evalbatchsize: 128
• —seed: 33
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 15
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.19.1
• —Pytorch 1.11.0+cu113
• —Datasets 2.2.1
• —Tokenizers 0.12.1