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phi-2-crime-vs-no-crime-classification
edvaldomelo/phi-2-crime-vs-no-crime-classification
phi-2-crime-vs-no-crime-classification is a text classification model from edvaldomelo. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- phi
- Access
- Public
- Created
- Oct 8, 2025
- Updated
- Oct 8, 2025
- SHA
- 5d369567
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
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
- Task
- Text Classification
- Library
- transformers
- Type
- phi
- License
- mit
- Created
- Oct 8, 2025
- Updated
- Oct 8, 2025