NER-BERT-10KData – AI Model by mehmetalpy | AlphaNeural AI

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mehmetalpy/
NER-BERT-10KData

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google-bert/bert-base-uncased

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NER-BERT-10KData

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

Loss: 0.4232

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: 0.0003
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
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss
0.2951	2.3256	100	0.4395
0.1989	4.6512	200	0.4701
0.1302	6.9767	300	0.4402
0.0967	9.3023	400	0.4868
0.0603	11.6279	500	0.4259
0.0365	13.9535	600	0.4508
0.0168	16.2791	700	0.4267
0.0119	18.6047	800	0.4077
0.0054	20.9302	900	0.4196
0.0027	23.2558	1000	0.4232

Framework versions

Transformers 4.44.0
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1