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_3
results: []
best_bert_model_fold_3
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: 1.2908
- Accuracy: 0.8386
- Precision: 0.8281
- Recall: 0.7986
- F1: 0.8101
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 | 0.6290 | 0.8008 | 0.7903 | 0.7322 | 0.7457 |
| 0.5166 | 2.0 | 504 | 0.6945 | 0.8068 | 0.8131 | 0.7396 | 0.7568 |
| 0.5166 | 3.0 | 756 | 0.9795 | 0.8108 | 0.7953 | 0.7652 | 0.7721 |
| 0.1546 | 4.0 | 1008 | 1.1504 | 0.8187 | 0.8024 | 0.7829 | 0.7902 |
| 0.1546 | 5.0 | 1260 | 1.2908 | 0.8386 | 0.8281 | 0.7986 | 0.8101 |
| 0.0243 | 6.0 | 1512 | 1.2868 | 0.8247 | 0.8043 | 0.7947 | 0.7988 |
| 0.0243 | 7.0 | 1764 | 1.4339 | 0.8307 | 0.8214 | 0.7823 | 0.7949 |
| 0.0077 | 8.0 | 2016 | 1.4287 | 0.8327 | 0.8222 | 0.7845 | 0.7978 |
| 0.0077 | 9.0 | 2268 | 1.4630 | 0.8287 | 0.8098 | 0.7842 | 0.7941 |
| 0.0001 | 10.0 | 2520 | 1.4618 | 0.8307 | 0.8129 | 0.7863 | 0.7966 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1