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phi-2-crime-vs-no-crime-classification – AI Model by edvaldomelo | AlphaNeural AI
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phi-2-crime-vs-no-crime-classification
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transformers
safetensors
phi
text-classification
generated_from_trainer
microsoft/phi-2
finetune
mit
endpoints_compatible
us
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phi-2-crime-vs-no-crime-classification
This model is a fine-tuned version of
microsoft/phi-2
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1690
Accuracy: 0.9411
Auc: 0.9843
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: 0.000352
train_batch_size: 6
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.056668
num_epochs: 10
Training results
Framework versions
Transformers 4.56.2
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
