---
library_name: transformers
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-turkish-cased_hate_span_detection_final
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-turkish-cased_hate_span_detection_final

This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4984
- Precision: 0.3858
- Recall: 0.4441
- F1: 0.4129
- Accuracy: 0.9018

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 62   | 0.2853          | 0.3103    | 0.3648 | 0.3354 | 0.8888   |
| 0.3754        | 2.0   | 124  | 0.2557          | 0.3672    | 0.4783 | 0.4155 | 0.8958   |
| 0.3754        | 3.0   | 186  | 0.2704          | 0.3920    | 0.4983 | 0.4388 | 0.8972   |
| 0.1772        | 4.0   | 248  | 0.2925          | 0.4431    | 0.5028 | 0.4711 | 0.9023   |
| 0.096         | 5.0   | 310  | 0.3442          | 0.4179    | 0.5184 | 0.4628 | 0.8984   |
| 0.096         | 6.0   | 372  | 0.3654          | 0.4395    | 0.5295 | 0.4803 | 0.9018   |
| 0.0607        | 7.0   | 434  | 0.3743          | 0.4698    | 0.5184 | 0.4929 | 0.9063   |
| 0.0607        | 8.0   | 496  | 0.4196          | 0.4614    | 0.5250 | 0.4912 | 0.9059   |
| 0.0429        | 9.0   | 558  | 0.4325          | 0.4472    | 0.5417 | 0.4899 | 0.9025   |
| 0.0298        | 10.0  | 620  | 0.4474          | 0.4609    | 0.5373 | 0.4961 | 0.9040   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0