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BERT-Finetuned-NER – AI Model by Mehmood-Deshmukh | AlphaNeural AI
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Mehmood-Deshmukh
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BERT-Finetuned-NER
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tensorboard
safetensors
bert
generated_from_trainer
conll2003
google-bert/bert-base-cased
finetune
apache-2.0
model-index
us
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test-ner
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: 0.0625
Accuracy: 0.9843
Precision: 0.9538
Recall: 0.9606
F1: 0.9572
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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.2406
1.0
878
0.0700
0.9792
0.9365
0.9471
0.9417
0.0485
2.0
1756
0.0663
0.9829
0.9486
0.9566
0.9526
0.026
3.0
2634
0.0625
0.9843
0.9538
0.9606
0.9572
Framework versions
Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
