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bert-base-ner-5 – AI Model by JohnLei | AlphaNeural AI
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JohnLei
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bert-base-ner-5
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
conll2003
google-bert/bert-base-cased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-base-ner-5
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: 1.9119
Precision: 0.0205
Recall: 0.0443
F1: 0.0280
Accuracy: 0.6152
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: 8
eval_batch_size: 8
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
3
2.0874
0.0189
0.0873
0.0311
0.2981
No log
2.0
6
1.9620
0.0195
0.0552
0.0288
0.5350
No log
3.0
9
1.9119
0.0205
0.0443
0.0280
0.6152
Framework versions
Transformers 4.51.2
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
