---
language:
- tr
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- Toygar/turkish-offensive-language-detection
metrics:
- accuracy
base_model: distilbert/distilbert-base-uncased
model-index:
- name: Distilbert Base Uncased Turkish Offensive Language Classifier - Atakan Ince
  results: []
---

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# Distilbert Base Uncased Turkish Offensive Language Classifier - Atakan Ince

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the Turkish Offensive Language Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2440
- Accuracy: 0.9067

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3075        | 0.36  | 1000 | 0.2871          | 0.8901   |
| 0.2652        | 0.72  | 2000 | 0.2520          | 0.9031   |
| 0.2825        | 1.09  | 3000 | 0.2506          | 0.9007   |
| 0.2471        | 1.45  | 4000 | 0.2440          | 0.9067   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2