22best_berita_bert_model_fold_1
This model is a fine-tuned version of ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3730
- Accuracy: 0.8302
- Precision: 0.8319
- Recall: 0.8468
- F1: 0.8309
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 | 106 | 0.7262 | 0.7123 | 0.7513 | 0.7032 | 0.6764 |
No log | 2.0 | 212 | 0.6140 | 0.8019 | 0.8154 | 0.8273 | 0.8032 |
No log | 3.0 | 318 | 1.0427 | 0.7594 | 0.7665 | 0.7740 | 0.7618 |
No log | 4.0 | 424 | 0.9092 | 0.8208 | 0.8191 | 0.8333 | 0.8214 |
0.4074 | 5.0 | 530 | 1.4762 | 0.7830 | 0.8110 | 0.8148 | 0.7838 |
0.4074 | 6.0 | 636 | 1.3960 | 0.7925 | 0.7954 | 0.8034 | 0.7923 |
0.4074 | 7.0 | 742 | 1.3455 | 0.8255 | 0.8282 | 0.8421 | 0.8258 |
0.4074 | 8.0 | 848 | 1.3730 | 0.8302 | 0.8319 | 0.8468 | 0.8309 |
0.4074 | 9.0 | 954 | 1.3804 | 0.8302 | 0.8319 | 0.8468 | 0.8309 |
0.0158 | 10.0 | 1060 | 1.3823 | 0.8302 | 0.8319 | 0.8468 | 0.8309 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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