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bert-finetuned-ner – AI Model by shimogerald | AlphaNeural AI
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shimogerald
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bert-finetuned-ner
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transformers
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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bert-finetuned-ner
This model is a fine-tuned version of
bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0522
Precision: 0.9421
Recall: 0.9505
F1: 0.9463
Accuracy: 0.9892
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0642
1.0
1756
0.0467
0.9358
0.9392
0.9375
0.9876
0.0285
2.0
3512
0.0511
0.9374
0.9497
0.9435
0.9883
0.0152
3.0
5268
0.0522
0.9421
0.9505
0.9463
0.9892
Framework versions
Transformers 5.12.0
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
