bert-finetuned-ner-synonym-replacement-model

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bert-finetuned-ner-synonym-replacement-model

This model is a fine-tuned version of bert-base-cased on the combined training dataset(tweetner7(train_2021)+augmented dataset(train_2021) using synonym replacment technique (lsoni/combined_tweetner7_synonym_replacement_augmented_dataset) and dataset used for evaluation is combined evaluation dataset(tweetner7(validation_2021)+augmented dataset(validation_2021) using synonym replacment technique (lsoni/combined_tweetner7_synonym_replacement_augmented_dataset_eval). It achieves the following results on the evaluation set:

• Loss: 0.4484
• Precision: 0.6804
• Recall: 0.6727
• F1: 0.6765
• Accuracy: 0.8780

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 4.20.1
• Pytorch 1.12.1
• Datasets 2.10.1
• Tokenizers 0.12.1