large-bert-cased-ner-finetuned-wikineural-final

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0692
• Precision: 0.9032
• Recall: 0.9117
• F1: 0.9075
• Accuracy: 0.9857

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: 9
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0273	1.0	10321	0.0692	0.9032	0.9117	0.9075	0.9857

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1