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--- |
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license: mit |
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base_model: burakaytan/roberta-base-turkish-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: laptop_kriter |
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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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# laptop_kriter |
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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: 0.2151 |
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- F1: 0.7709 |
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- Roc Auc: 0.8574 |
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- Accuracy: 0.7344 |
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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: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:| |
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| 0.3066 | 1.0 | 1151 | 0.2457 | 0.5688 | 0.7257 | 0.6484 | |
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| 0.2325 | 2.0 | 2302 | 0.2088 | 0.6630 | 0.7908 | 0.6719 | |
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| 0.1723 | 3.0 | 3453 | 0.2023 | 0.6933 | 0.8174 | 0.6875 | |
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| 0.159 | 4.0 | 4604 | 0.2004 | 0.7312 | 0.8363 | 0.7188 | |
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| 0.1306 | 5.0 | 5755 | 0.2138 | 0.7168 | 0.8104 | 0.7148 | |
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| 0.1034 | 6.0 | 6906 | 0.2103 | 0.7745 | 0.8641 | 0.7539 | |
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| 0.0865 | 7.0 | 8057 | 0.2107 | 0.7684 | 0.8530 | 0.75 | |
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| 0.0733 | 8.0 | 9208 | 0.2099 | 0.7757 | 0.8663 | 0.7383 | |
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| 0.0643 | 9.0 | 10359 | 0.2130 | 0.7772 | 0.8586 | 0.7539 | |
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| 0.0617 | 10.0 | 11510 | 0.2151 | 0.7709 | 0.8574 | 0.7344 | |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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