bert-finetuned-semantic-augmentation-ner

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bert-finetuned-semantic-augmentation-ner

This model is a fine-tuned version of tner/roberta-base-tweetner7-2021 on the tweetner7 dataset. It achieves the following results on the evaluation set:

• Loss: 0.7890
• Precision: 0.7156
• Recall: 0.7215
• F1: 0.7185
• Accuracy: 0.8840

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: 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 4.31.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.1
• Tokenizers 0.13.3