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---
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_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_roberta_model_fold_3
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: 0.6566
- Accuracy: 0.8566
- Precision: 0.8385
- Recall: 0.8215
- F1: 0.8286
## 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 | 0.6056 | 0.8307 | 0.8493 | 0.7768 | 0.7998 |
| 0.4224 | 2.0 | 504 | 0.6566 | 0.8566 | 0.8385 | 0.8215 | 0.8286 |
| 0.4224 | 3.0 | 756 | 0.8546 | 0.8506 | 0.8410 | 0.8094 | 0.8211 |
| 0.1153 | 4.0 | 1008 | 0.9318 | 0.8446 | 0.8220 | 0.8093 | 0.8146 |
| 0.1153 | 5.0 | 1260 | 1.0414 | 0.8367 | 0.8297 | 0.7856 | 0.7984 |
| 0.0403 | 6.0 | 1512 | 1.1900 | 0.8327 | 0.8118 | 0.7848 | 0.7945 |
| 0.0403 | 7.0 | 1764 | 1.1295 | 0.8406 | 0.8143 | 0.8041 | 0.8086 |
| 0.0107 | 8.0 | 2016 | 1.2422 | 0.8327 | 0.8164 | 0.7927 | 0.8004 |
| 0.0107 | 9.0 | 2268 | 1.1965 | 0.8386 | 0.8170 | 0.8013 | 0.8079 |
| 0.0003 | 10.0 | 2520 | 1.2360 | 0.8426 | 0.8212 | 0.8025 | 0.8103 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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