|
--- |
|
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: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# best_bert_model_fold_3 |
|
|
|
This model is a fine-tuned version of [ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa](https://huggingface.co/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 |
|
|
