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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: roberta-news-classifier
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# roberta-news-classifier
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.2394
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- Accuracy: 0.9388
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- F1: 0.9388
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- Precision: 0.9388
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- Recall: 0.9388
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 64
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- eval_batch_size: 150
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 12
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.2929 | 1.0 | 62 | 0.2893 | 0.9316 | 0.9316 | 0.9316 | 0.9316 |
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| 0.2775 | 2.0 | 124 | 0.2700 | 0.9337 | 0.9337 | 0.9337 | 0.9337 |
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| 0.2554 | 3.0 | 186 | 0.2576 | 0.9286 | 0.9286 | 0.9286 | 0.9286 |
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| 0.2198 | 4.0 | 248 | 0.2409 | 0.9286 | 0.9286 | 0.9286 | 0.9286 |
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| 0.197 | 5.0 | 310 | 0.2324 | 0.9306 | 0.9306 | 0.9306 | 0.9306 |
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| 0.1611 | 6.0 | 372 | 0.2254 | 0.9367 | 0.9367 | 0.9367 | 0.9367 |
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| 0.1302 | 7.0 | 434 | 0.2204 | 0.9378 | 0.9378 | 0.9378 | 0.9378 |
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| 0.1058 | 8.0 | 496 | 0.2238 | 0.9337 | 0.9337 | 0.9337 | 0.9337 |
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| 0.0976 | 9.0 | 558 | 0.2295 | 0.9378 | 0.9378 | 0.9378 | 0.9378 |
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| 0.0795 | 10.0 | 620 | 0.2299 | 0.9378 | 0.9378 | 0.9378 | 0.9378 |
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| 0.0641 | 11.0 | 682 | 0.2394 | 0.9388 | 0.9388 | 0.9388 | 0.9388 |
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| 0.0544 | 12.0 | 744 | 0.2392 | 0.9367 | 0.9367 | 0.9367 | 0.9367 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.12.1+cu113
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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