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sxored-be-bankstatementcategorizer – AI Model by sxored | AlphaNeural AI
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sxored-be-bankstatementcategorizer
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transformers
safetensors
bert
text-classification
generated_from_trainer
cahya/bert-base-indonesian-1.5G
finetune
mit
text-embeddings-inference
endpoints_compatible
us
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sxored-be-bankstatementcategorizer
This model is a fine-tuned version of
cahya/bert-base-indonesian-1.5G
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0262
Accuracy: 0.9843
F1: 0.9858
Precision: 0.9884
Recall: 0.9843
Roc Auc: 0.9994
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: 10
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.57.3
Pytorch 2.6.0+cu124
Datasets 4.4.2
Tokenizers 0.22.1
