5e-05_32_5_detect / README.md
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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: 5e-05_32_5_detect
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. -->
# 5e-05_32_5_detect
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: 0.3045
- Precision: 0.5046
- Recall: 0.3838
- F1: 0.4360
- Accuracy: 0.8908
## 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: 32
- eval_batch_size: 32
- 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 76 | 0.1080 | 0.5529 | 0.5629 | 0.5579 | 0.9701 |
| 0.2181 | 2.0 | 152 | 0.1084 | 0.3954 | 0.6228 | 0.4837 | 0.9626 |
| 0.0781 | 3.0 | 228 | 0.1120 | 0.5497 | 0.4970 | 0.5220 | 0.9687 |
| 0.0336 | 4.0 | 304 | 0.1083 | 0.4328 | 0.6168 | 0.5086 | 0.9647 |
### Framework versions
- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0