|
--- |
|
license: mit |
|
base_model: ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
- f1 |
|
model-index: |
|
- name: best_berita_roberta_model_fold_5 |
|
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. --> |
|
|
|
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>]() |
|
# best_berita_roberta_model_fold_5 |
|
|
|
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: 0.1318 |
|
- Accuracy: 0.9808 |
|
- Precision: 0.9811 |
|
- Recall: 0.9807 |
|
- F1: 0.9807 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
| 0.5679 | 1.0 | 601 | 0.1942 | 0.9425 | 0.9449 | 0.9419 | 0.9419 | |
|
| 0.2491 | 2.0 | 1202 | 0.1654 | 0.9692 | 0.9691 | 0.9694 | 0.9691 | |
|
| 0.1085 | 3.0 | 1803 | 0.1314 | 0.9742 | 0.9743 | 0.9741 | 0.9740 | |
|
| 0.074 | 4.0 | 2404 | 0.2535 | 0.9575 | 0.9604 | 0.9568 | 0.9564 | |
|
| 0.0255 | 5.0 | 3005 | 0.1318 | 0.9808 | 0.9811 | 0.9807 | 0.9807 | |
|
| 0.0164 | 6.0 | 3606 | 0.1795 | 0.9759 | 0.9762 | 0.9756 | 0.9756 | |
|
| 0.0 | 7.0 | 4207 | 0.2299 | 0.9725 | 0.9730 | 0.9723 | 0.9721 | |
|
| 0.0039 | 8.0 | 4808 | 0.2241 | 0.9717 | 0.9723 | 0.9714 | 0.9713 | |
|
| 0.0048 | 9.0 | 5409 | 0.2199 | 0.9717 | 0.9723 | 0.9714 | 0.9713 | |
|
| 0.0 | 10.0 | 6010 | 0.2303 | 0.9717 | 0.9723 | 0.9714 | 0.9713 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.3 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
