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---
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 |