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brand_ner_model – AI Model by sianbrumm | AlphaNeural AI
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brand_ner_model
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transformers
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-german-cased
finetune
mit
autotrain_compatible
endpoints_compatible
us
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brand_ner_model
This model is a fine-tuned version of
bert-base-german-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0132
Brand: {'precision': 0.9935705381940648, 'recall': 0.9933967421012354, 'f1': 0.99348363254685, 'number': 45735}
Overall Precision: 0.9936
Overall Recall: 0.9934
Overall F1: 0.9935
Overall Accuracy: 0.9974
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: 32
eval_batch_size: 32
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: 4
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.52.4
Pytorch 2.7.0+cu118
Datasets 3.6.0
Tokenizers 0.21.1
