lsoni/bert-finetuned-ner-word-embedding

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bert-finetuned-ner-word-embedding

This model is a fine-tuned version of bert-base-cased on the combined training dataset(tweetner7(train2021)+augmented dataset(train2021) using word embedding technique). It achieves the following results on the evaluation set:

• —Loss: 0.5502
• —Precision: 0.6522
• —Recall: 0.4973
• —F1: 0.5643
• —Accuracy: 0.8615

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 4.20.1
• —Pytorch 1.12.1
• —Datasets 2.10.1
• —Tokenizers 0.12.1