bert-finetuned-ner – AI Model by tarasz98 | AlphaNeural AI

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tarasz98/
bert-finetuned-ner

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token-classification

generated_from_trainer

google-bert/bert-base-cased

endpoints_compatible

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bert-finetuned-ner

This model is a fine-tuned version of bert-base-cased on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.0770
Precision: 0.9391
Recall: 0.9544
F1: 0.9467
Accuracy: 0.9872

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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0691	1.0	1756	0.0730	0.8998	0.9307	0.9150	0.9801
0.0292	2.0	3512	0.0780	0.9307	0.9398	0.9352	0.9840
0.0176	3.0	5268	0.0682	0.9355	0.9512	0.9433	0.9866
0.0099	4.0	7024	0.0763	0.9366	0.9547	0.9456	0.9872
0.0051	5.0	8780	0.0770	0.9391	0.9544	0.9467	0.9872

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 3.6.0
Tokenizers 0.22.1