bert-base-NER-5 – AI Model by wwwtwwwt | AlphaNeural AI

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bert-base-NER-5

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token-classification

generated_from_trainer

google-bert/bert-base-cased

autotrain_compatible

endpoints_compatible

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bert-base-NER-5

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: 1.9564
Precision: 0.0116
Recall: 0.0522
F1: 0.0190
Accuracy: 0.3588

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	1	2.0364	0.0149	0.0875	0.0254	0.2246
No log	2.0	2	1.9827	0.0125	0.0623	0.0209	0.3118
No log	3.0	3	1.9564	0.0116	0.0522	0.0190	0.3588

Framework versions

Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0