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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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