--- library_name: transformers license: mit base_model: w11wo/indonesian-roberta-base-sentiment-classifier tags: - generated_from_trainer metrics: - accuracy model-index: - name: results_final results: [] --- # results_final This model is a fine-tuned version of [w11wo/indonesian-roberta-base-sentiment-classifier](https://huggingface.co/w11wo/indonesian-roberta-base-sentiment-classifier) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4292 - Accuracy: 0.8881 - F1 Macro: 0.8880 - F1 Weighted: 0.8880 - Precision Macro: 0.8896 - Recall Macro: 0.8881 - Precision Weighted: 0.8895 - Recall Weighted: 0.8881 ## 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: 3e-06 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro | Precision Weighted | Recall Weighted | |:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:------------:|:------------------:|:---------------:| | 0.2316 | 0.3436 | 100 | 0.4071 | 0.8864 | 0.8862 | 0.8862 | 0.8869 | 0.8864 | 0.8870 | 0.8864 | | 0.2298 | 0.6873 | 200 | 0.4028 | 0.8864 | 0.8863 | 0.8863 | 0.8867 | 0.8864 | 0.8867 | 0.8864 | | 0.1311 | 1.0309 | 300 | 0.4144 | 0.8847 | 0.8846 | 0.8846 | 0.8852 | 0.8847 | 0.8852 | 0.8847 | | 0.159 | 1.3746 | 400 | 0.4292 | 0.8881 | 0.8880 | 0.8880 | 0.8896 | 0.8881 | 0.8895 | 0.8881 | | 0.1957 | 1.7182 | 500 | 0.4283 | 0.8830 | 0.8828 | 0.8829 | 0.8835 | 0.8829 | 0.8836 | 0.8830 | | 0.228 | 2.0619 | 600 | 0.4153 | 0.8778 | 0.8778 | 0.8779 | 0.8783 | 0.8778 | 0.8783 | 0.8778 | | 0.2248 | 2.4055 | 700 | 0.4242 | 0.8830 | 0.8828 | 0.8828 | 0.8833 | 0.8829 | 0.8833 | 0.8830 | | 0.1733 | 2.7491 | 800 | 0.4239 | 0.8795 | 0.8795 | 0.8795 | 0.8803 | 0.8795 | 0.8803 | 0.8795 | | 0.2314 | 3.0928 | 900 | 0.4166 | 0.8812 | 0.8811 | 0.8811 | 0.8813 | 0.8812 | 0.8813 | 0.8812 | | 0.1691 | 3.4364 | 1000 | 0.4472 | 0.8744 | 0.8741 | 0.8741 | 0.8757 | 0.8743 | 0.8757 | 0.8744 | | 0.2671 | 3.7801 | 1100 | 0.4273 | 0.8830 | 0.8828 | 0.8829 | 0.8832 | 0.8829 | 0.8832 | 0.8830 | | 0.2643 | 4.1237 | 1200 | 0.4317 | 0.8812 | 0.8811 | 0.8811 | 0.8815 | 0.8812 | 0.8815 | 0.8812 | | 0.202 | 4.4674 | 1300 | 0.4440 | 0.8847 | 0.8846 | 0.8846 | 0.8852 | 0.8846 | 0.8852 | 0.8847 | | 0.2538 | 4.8110 | 1400 | 0.4397 | 0.8812 | 0.8812 | 0.8812 | 0.8816 | 0.8812 | 0.8816 | 0.8812 | | 0.2662 | 5.1546 | 1500 | 0.4364 | 0.8847 | 0.8846 | 0.8846 | 0.8852 | 0.8846 | 0.8852 | 0.8847 | | 0.2655 | 5.4983 | 1600 | 0.4298 | 0.8812 | 0.8812 | 0.8812 | 0.8816 | 0.8812 | 0.8816 | 0.8812 | | 0.1933 | 5.8419 | 1700 | 0.4422 | 0.8847 | 0.8845 | 0.8845 | 0.8854 | 0.8846 | 0.8854 | 0.8847 | | 0.2289 | 6.1856 | 1800 | 0.4282 | 0.8778 | 0.8776 | 0.8777 | 0.8778 | 0.8778 | 0.8778 | 0.8778 | | 0.2298 | 6.5292 | 1900 | 0.4313 | 0.8795 | 0.8794 | 0.8794 | 0.8798 | 0.8795 | 0.8798 | 0.8795 | | 0.2008 | 6.8729 | 2000 | 0.4344 | 0.8812 | 0.8811 | 0.8812 | 0.8816 | 0.8812 | 0.8817 | 0.8812 | | 0.2107 | 7.2165 | 2100 | 0.4354 | 0.8830 | 0.8829 | 0.8829 | 0.8833 | 0.8829 | 0.8834 | 0.8830 | | 0.2505 | 7.5601 | 2200 | 0.4353 | 0.8830 | 0.8829 | 0.8829 | 0.8833 | 0.8829 | 0.8834 | 0.8830 | | 0.2134 | 7.9038 | 2300 | 0.4361 | 0.8830 | 0.8829 | 0.8829 | 0.8833 | 0.8829 | 0.8834 | 0.8830 | | 0.2613 | 8.2474 | 2400 | 0.4344 | 0.8830 | 0.8828 | 0.8829 | 0.8832 | 0.8829 | 0.8832 | 0.8830 | | 0.2128 | 8.5911 | 2500 | 0.4350 | 0.8830 | 0.8828 | 0.8829 | 0.8832 | 0.8829 | 0.8832 | 0.8830 | | 0.212 | 8.9347 | 2600 | 0.4356 | 0.8830 | 0.8828 | 0.8829 | 0.8832 | 0.8829 | 0.8832 | 0.8830 | | 0.2379 | 9.2784 | 2700 | 0.4359 | 0.8830 | 0.8828 | 0.8829 | 0.8832 | 0.8829 | 0.8832 | 0.8830 | | 0.1471 | 9.6220 | 2800 | 0.4358 | 0.8830 | 0.8828 | 0.8829 | 0.8832 | 0.8829 | 0.8832 | 0.8830 | | 0.1781 | 9.9656 | 2900 | 0.4359 | 0.8830 | 0.8828 | 0.8829 | 0.8832 | 0.8829 | 0.8832 | 0.8830 | ### Framework versions - Transformers 4.51.3 - Pytorch 2.6.0+cu124 - Datasets 2.14.4 - Tokenizers 0.21.1