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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-news-classifier
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. -->
# roberta-news-classifier
This model is a fine-tuned version of [burakaytan/roberta-base-turkish-uncased](https://huggingface.co/burakaytan/roberta-base-turkish-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2394
- Accuracy: 0.9388
- F1: 0.9388
- Precision: 0.9388
- Recall: 0.9388
## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 150
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2929 | 1.0 | 62 | 0.2893 | 0.9316 | 0.9316 | 0.9316 | 0.9316 |
| 0.2775 | 2.0 | 124 | 0.2700 | 0.9337 | 0.9337 | 0.9337 | 0.9337 |
| 0.2554 | 3.0 | 186 | 0.2576 | 0.9286 | 0.9286 | 0.9286 | 0.9286 |
| 0.2198 | 4.0 | 248 | 0.2409 | 0.9286 | 0.9286 | 0.9286 | 0.9286 |
| 0.197 | 5.0 | 310 | 0.2324 | 0.9306 | 0.9306 | 0.9306 | 0.9306 |
| 0.1611 | 6.0 | 372 | 0.2254 | 0.9367 | 0.9367 | 0.9367 | 0.9367 |
| 0.1302 | 7.0 | 434 | 0.2204 | 0.9378 | 0.9378 | 0.9378 | 0.9378 |
| 0.1058 | 8.0 | 496 | 0.2238 | 0.9337 | 0.9337 | 0.9337 | 0.9337 |
| 0.0976 | 9.0 | 558 | 0.2295 | 0.9378 | 0.9378 | 0.9378 | 0.9378 |
| 0.0795 | 10.0 | 620 | 0.2299 | 0.9378 | 0.9378 | 0.9378 | 0.9378 |
| 0.0641 | 11.0 | 682 | 0.2394 | 0.9388 | 0.9388 | 0.9388 | 0.9388 |
| 0.0544 | 12.0 | 744 | 0.2392 | 0.9367 | 0.9367 | 0.9367 | 0.9367 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
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