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--- |
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license: mit |
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base_model: ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: best_berita_roberta_model_fold_3 |
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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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# best_berita_roberta_model_fold_3 |
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This model is a fine-tuned version of [ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa](https://huggingface.co/ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1247 |
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- Accuracy: 0.9833 |
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- Precision: 0.9833 |
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- Recall: 0.9836 |
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- F1: 0.9834 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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 | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.5662 | 1.0 | 601 | 0.3954 | 0.9142 | 0.9181 | 0.9155 | 0.9140 | |
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| 0.2162 | 2.0 | 1202 | 0.2580 | 0.9525 | 0.9532 | 0.9532 | 0.9525 | |
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| 0.1503 | 3.0 | 1803 | 0.1226 | 0.9825 | 0.9826 | 0.9827 | 0.9826 | |
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| 0.0849 | 4.0 | 2404 | 0.3352 | 0.9609 | 0.9615 | 0.9615 | 0.9609 | |
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| 0.0257 | 5.0 | 3005 | 0.1938 | 0.9725 | 0.9728 | 0.9730 | 0.9725 | |
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| 0.0277 | 6.0 | 3606 | 0.1247 | 0.9833 | 0.9833 | 0.9836 | 0.9834 | |
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| 0.0123 | 7.0 | 4207 | 0.1741 | 0.9800 | 0.9801 | 0.9803 | 0.9800 | |
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| 0.0061 | 8.0 | 4808 | 0.1870 | 0.9792 | 0.9793 | 0.9795 | 0.9792 | |
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| 0.0 | 9.0 | 5409 | 0.1793 | 0.9817 | 0.9817 | 0.9820 | 0.9817 | |
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| 0.0 | 10.0 | 6010 | 0.1802 | 0.9817 | 0.9817 | 0.9820 | 0.9817 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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