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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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