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bert-NER-5 – AI Model by wwwtwwwt | AlphaNeural AI
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bert-NER-5
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
conll2003
google-bert/bert-large-cased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-NER-5
This model is a fine-tuned version of
bert-large-cased
on the conll2003 dataset. It achieves the following results on the evaluation set:
Loss: 1.9971
Precision: 0.0202
Recall: 0.0916
F1: 0.0331
Accuracy: 0.3502
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
2.2042
0.0170
0.1035
0.0292
0.1450
No log
2.0
2
2.0652
0.0175
0.0899
0.0292
0.2699
No log
3.0
3
1.9971
0.0202
0.0916
0.0331
0.3502
Framework versions
Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0
