best_roberta_model_fold_2
This model is a fine-tuned version of 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
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