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bert-finetuned-ner – AI Model by 3EsTarek | AlphaNeural AI
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3EsTarek
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bert-finetuned-ner
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transformers
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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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: 0.1149
Precision: 0.5729
Recall: 0.5787
F1: 0.5758
Accuracy: 0.9806
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 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
5
0.2606
0.0
0.0
0.0
0.9360
No log
2.0
10
0.1431
0.3116
0.3147
0.3131
0.9685
No log
3.0
15
0.1149
0.5729
0.5787
0.5758
0.9806
Framework versions
Transformers 4.50.1
Pytorch 2.6.0+cpu
Datasets 3.4.1
Tokenizers 0.21.1
