Tagged_One_250v3_NER_Model_3Epochs_AUGMENTED

This model is a fine-tuned version of bert-base-cased on the tagged_one250v3_wikigold_split dataset. It achieves the following results on the evaluation set:

• Loss: 0.3179
• Precision: 0.5783
• Recall: 0.4806
• F1: 0.5250
• Accuracy: 0.8982

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

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	81	0.3974	0.2778	0.1869	0.2235	0.8530
No log	2.0	162	0.3095	0.5594	0.4470	0.4969	0.8944
No log	3.0	243	0.3179	0.5783	0.4806	0.5250	0.8982

Framework versions

• Transformers 4.17.0
• Pytorch 1.11.0+cu113
• Datasets 2.4.0
• Tokenizers 0.11.6