bert-base-multilingual-cased_baseline_words

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bert-base-multilingual-cased_baseline_words

This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the covid19_ner dataset. It achieves the following results on the evaluation set:

• Loss: 0.0998
• Patient Id: 0.9840
• Name: 0.9182
• Gender: 0.9623
• Age: 0.9725
• Job: 0.7799
• Location: 0.9501
• Organization: 0.8965
• Date: 0.9869
• Symptom And Disease: 0.8626
• Transportation: 0.9885
• F1 Macro: 0.9302
• F1 Micro: 0.9466

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: 5

Training results

Framework versions

• Transformers 4.41.2
• Pytorch 2.1.2
• Datasets 2.19.2
• Tokenizers 0.19.1