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

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regorkaz/
bert-finetuned-ner

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token-classification

generated_from_trainer

BAAI/bge-small-en-v1.5

endpoints_compatible

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bert-finetuned-ner

This model is a fine-tuned version of BAAI/bge-small-en-v1.5 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0856
Precision: 0.8998
Recall: 0.9244
F1: 0.9119
Accuracy: 0.9813

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
0.0639	1.0	1250	0.0946	0.8626	0.9128	0.8870	0.9769
0.0452	2.0	2500	0.0885	0.8961	0.9189	0.9074	0.9803
0.0363	3.0	3750	0.0841	0.8882	0.9187	0.9032	0.9807
0.0291	4.0	5000	0.0868	0.9013	0.9238	0.9124	0.9812
0.0261	5.0	6250	0.0856	0.8998	0.9244	0.9119	0.9813

Framework versions

Transformers 4.57.0
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1