---
library_name: peft
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: turkish_hate_speech
  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. -->

# turkish_hate_speech

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3413
- Accuracy: 0.8566
- F1 Macro: 0.8564
- Precision Macro: 0.8612
- Recall Macro: 0.8580
- F1 Nefret: 0.8512
- F1 Hicbiri: 0.8615

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use paged_adamw_8bit 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: 0.01
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | F1 Nefret | F1 Hicbiri |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:---------:|:----------:|
| 0.5934        | 1.0   | 800  | 0.4766          | 0.7694   | 0.7670   | 0.7818          | 0.7697       | 0.7432    | 0.7907     |
| 0.4308        | 2.0   | 1600 | 0.3973          | 0.8184   | 0.8184   | 0.8186          | 0.8184       | 0.8212    | 0.8156     |
| 0.3898        | 3.0   | 2400 | 0.3548          | 0.8431   | 0.8430   | 0.8440          | 0.8432       | 0.8396    | 0.8465     |
| 0.3393        | 4.0   | 3200 | 0.3355          | 0.8538   | 0.8535   | 0.8566          | 0.8539       | 0.8474    | 0.8596     |
| 0.319         | 5.0   | 4000 | 0.3220          | 0.86     | 0.8600   | 0.8601          | 0.8600       | 0.8590    | 0.8610     |
| 0.3053        | 6.0   | 4800 | 0.3201          | 0.8641   | 0.8640   | 0.8654          | 0.8642       | 0.8603    | 0.8677     |
| 0.2887        | 7.0   | 5600 | 0.3166          | 0.8638   | 0.8634   | 0.8673          | 0.8639       | 0.8570    | 0.8699     |
| 0.2908        | 8.0   | 6400 | 0.3271          | 0.8634   | 0.8631   | 0.8679          | 0.8636       | 0.8559    | 0.8702     |
| 0.2764        | 9.0   | 7200 | 0.3207          | 0.8659   | 0.8657   | 0.8692          | 0.8661       | 0.8597    | 0.8717     |
| 0.2754        | 10.0  | 8000 | 0.3207          | 0.8656   | 0.8654   | 0.8689          | 0.8658       | 0.8594    | 0.8713     |


### Framework versions

- PEFT 0.15.1
- Transformers 4.50.3
- Pytorch 2.5.1+cu121
- Datasets 3.5.0
- Tokenizers 0.21.0