22best_berita_bert_model_fold_2
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: 1.2522
- Accuracy: 0.8349
- Precision: 0.8373
- Recall: 0.8357
- F1: 0.8333
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 | 0.6551 | 0.7264 | 0.7745 | 0.7082 | 0.7121 |
No log | 2.0 | 212 | 0.9467 | 0.6934 | 0.7488 | 0.7142 | 0.6839 |
No log | 3.0 | 318 | 0.8995 | 0.8113 | 0.8139 | 0.8146 | 0.8111 |
No log | 4.0 | 424 | 1.1543 | 0.7972 | 0.8169 | 0.7986 | 0.7936 |
0.3548 | 5.0 | 530 | 1.1540 | 0.8208 | 0.8223 | 0.8148 | 0.8169 |
0.3548 | 6.0 | 636 | 1.3006 | 0.8255 | 0.8431 | 0.8261 | 0.8225 |
0.3548 | 7.0 | 742 | 1.2421 | 0.8255 | 0.8328 | 0.8265 | 0.8240 |
0.3548 | 8.0 | 848 | 1.2522 | 0.8349 | 0.8373 | 0.8357 | 0.8333 |
0.3548 | 9.0 | 954 | 1.2637 | 0.8302 | 0.8330 | 0.8308 | 0.8285 |
0.0125 | 10.0 | 1060 | 1.2667 | 0.8302 | 0.8330 | 0.8308 | 0.8285 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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