|
--- |
|
license: mit |
|
base_model: ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
- f1 |
|
model-index: |
|
- name: best_roberta_model_fold_2 |
|
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_roberta_model_fold_2 |
|
|
|
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. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3694 |
|
- Accuracy: 0.8785 |
|
- Precision: 0.8509 |
|
- Recall: 0.8453 |
|
- F1: 0.8475 |
|
|
|
## 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 | 0.3694 | 0.8785 | 0.8509 | 0.8453 | 0.8475 | |
|
| 0.4624 | 2.0 | 504 | 0.6764 | 0.8506 | 0.8218 | 0.8193 | 0.8150 | |
|
| 0.4624 | 3.0 | 756 | 0.7159 | 0.8745 | 0.8644 | 0.8280 | 0.8431 | |
|
| 0.1511 | 4.0 | 1008 | 0.6390 | 0.8785 | 0.8689 | 0.8156 | 0.8345 | |
|
| 0.1511 | 5.0 | 1260 | 0.7848 | 0.8785 | 0.8594 | 0.8438 | 0.8506 | |
|
| 0.0503 | 6.0 | 1512 | 0.8157 | 0.8785 | 0.8544 | 0.8493 | 0.8512 | |
|
| 0.0503 | 7.0 | 1764 | 0.9260 | 0.8785 | 0.8600 | 0.8427 | 0.8488 | |
|
| 0.0103 | 8.0 | 2016 | 0.8872 | 0.8765 | 0.8526 | 0.8325 | 0.8415 | |
|
| 0.0103 | 9.0 | 2268 | 1.0181 | 0.8745 | 0.8552 | 0.8330 | 0.8422 | |
|
| 0.0006 | 10.0 | 2520 | 1.0201 | 0.8745 | 0.8542 | 0.8330 | 0.8418 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |
|
|
