---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: Criminal
  results: []
---

<!-- 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. -->

# Criminal

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4251
- Acc: 0.9172
- F1: 0.9167
- Precision: 0.9128
- Recall: 0.9206

## 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: 8
- 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: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Acc    | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
| 0.2608        | 1.0   | 535  | 0.2875          | 0.9193 | 0.9179 | 0.9245    | 0.9113 |
| 0.1115        | 2.0   | 1070 | 0.3404          | 0.9232 | 0.9234 | 0.9110    | 0.9362 |
| 0.0926        | 3.0   | 1605 | 0.3537          | 0.92   | 0.92   | 0.9104    | 0.9298 |
| 0.0459        | 4.0   | 2140 | 0.4191          | 0.9204 | 0.9188 | 0.9271    | 0.9106 |
| 0.019         | 5.0   | 2675 | 0.4251          | 0.9172 | 0.9167 | 0.9128    | 0.9206 |


### Framework versions

- Transformers 4.55.4
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4