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

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baltilucas/
bert-finetuned-ner

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token-classification

generated_from_trainer

google-bert/bert-base-cased

autotrain_compatible

endpoints_compatible

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bert-finetuned-ner

This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2962
Precision: 0.4571
Recall: 0.4646
F1: 0.4608
Accuracy: 0.8910

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: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	202	0.2687	0.4002	0.3466	0.3714	0.8816
No log	2.0	404	0.2490	0.4673	0.3992	0.4306	0.8957
0.2638	3.0	606	0.2730	0.4310	0.4418	0.4364	0.8852
0.2638	4.0	808	0.2808	0.4155	0.4637	0.4383	0.8823
0.1839	5.0	1010	0.3016	0.4285	0.4701	0.4483	0.8844
0.1839	6.0	1212	0.2962	0.4571	0.4646	0.4608	0.8910

Framework versions

Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.0.2
Tokenizers 0.19.1