best_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: 1.2379
- Accuracy: 0.8469
- Precision: 0.8335
- Recall: 0.8102
- F1: 0.8194
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 | 251 | 0.4965 | 0.8270 | 0.8015 | 0.7727 | 0.7833 |
| 0.5228 | 2.0 | 502 | 0.5798 | 0.7932 | 0.7579 | 0.7603 | 0.7583 |
| 0.5228 | 3.0 | 753 | 0.9632 | 0.8290 | 0.8267 | 0.7803 | 0.7969 |
| 0.1728 | 4.0 | 1004 | 1.3744 | 0.7714 | 0.7453 | 0.7690 | 0.7476 |
| 0.1728 | 5.0 | 1255 | 1.1893 | 0.8072 | 0.7791 | 0.7798 | 0.7772 |
| 0.0483 | 6.0 | 1506 | 1.2379 | 0.8469 | 0.8335 | 0.8102 | 0.8194 |
| 0.0483 | 7.0 | 1757 | 1.3635 | 0.8370 | 0.8185 | 0.8044 | 0.8081 |
| 0.0075 | 8.0 | 2008 | 1.3300 | 0.8370 | 0.8168 | 0.8008 | 0.8074 |
| 0.0075 | 9.0 | 2259 | 1.3591 | 0.8410 | 0.8249 | 0.8074 | 0.8142 |
| 0.0026 | 10.0 | 2510 | 1.3548 | 0.8350 | 0.8169 | 0.8008 | 0.8072 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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