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bert-finetuned-ner – AI Model by alessandrodotf | AlphaNeural AI
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bert-finetuned-ner
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transformers
safetensors
bert
token-classification
generated_from_trainer
conll2003
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 conll2003 dataset.
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: 64
eval_batch_size: 64
seed: 42
optimizer: Use 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: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
220
0.0593
0.9150
0.9426
0.9286
0.9847
Framework versions
Transformers 4.49.0
Pytorch 2.6.0+cu118
Datasets 3.3.2
Tokenizers 0.21.0
