metadata
license: mit
base_model: ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: best_bert_model_fold_4
results: []
best_bert_model_fold_4
This model is a fine-tuned version of ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6077
- Accuracy: 0.8187
- Precision: 0.7940
- Recall: 0.7673
- F1: 0.7780
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 252 | 0.5413 | 0.8088 | 0.7842 | 0.7520 | 0.7641 |
| 0.5338 | 2.0 | 504 | 0.6077 | 0.8187 | 0.7940 | 0.7673 | 0.7780 |
| 0.5338 | 3.0 | 756 | 0.9325 | 0.7928 | 0.7597 | 0.7270 | 0.7357 |
| 0.1829 | 4.0 | 1008 | 1.1287 | 0.8068 | 0.7916 | 0.7662 | 0.7763 |
| 0.1829 | 5.0 | 1260 | 1.2985 | 0.7988 | 0.7700 | 0.7688 | 0.7676 |
| 0.0459 | 6.0 | 1512 | 1.5210 | 0.8108 | 0.7837 | 0.7721 | 0.7773 |
| 0.0459 | 7.0 | 1764 | 1.5855 | 0.8028 | 0.7799 | 0.7611 | 0.7680 |
| 0.0097 | 8.0 | 2016 | 1.5212 | 0.8008 | 0.7684 | 0.7731 | 0.7706 |
| 0.0097 | 9.0 | 2268 | 1.5775 | 0.8028 | 0.7730 | 0.7656 | 0.7682 |
| 0.0001 | 10.0 | 2520 | 1.5819 | 0.8048 | 0.7746 | 0.7669 | 0.7698 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1