uner-bert-ner – AI Model by mirfan899 | AlphaNeural AI

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mirfan899/
uner-bert-ner

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token-classification

generated_from_trainer

google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

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uner-bert-ner

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

Loss: 0.1354
Precision: 0.8267
Recall: 0.8707
F1: 0.8481
Accuracy: 0.9640

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	144	0.1496	0.7687	0.7971	0.7826	0.9533
No log	2.0	288	0.1429	0.7719	0.8584	0.8129	0.9573
No log	3.0	432	0.1267	0.8014	0.8682	0.8335	0.9629
0.1628	4.0	576	0.1316	0.8206	0.8723	0.8457	0.9644
0.1628	5.0	720	0.1354	0.8267	0.8707	0.8481	0.9640

Framework versions

Transformers 4.33.0
Pytorch 2.0.0
Datasets 2.14.5
Tokenizers 0.13.3