indobert-post-training-fin-sa-7
This model is a fine-tuned version of elidle/indobert-fin_news-mlm-3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2290
- Accuracy: 0.9647
- F1: 0.9647
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1566 | 1.0 | 102 | 0.2478 | 0.9286 | 0.9293 |
| 0.0339 | 2.0 | 204 | 0.2647 | 0.9341 | 0.9318 |
| 0.0362 | 3.0 | 306 | 0.2665 | 0.9451 | 0.9444 |
| 0.0682 | 4.0 | 408 | 0.2679 | 0.9451 | 0.9449 |
| 0.0287 | 5.0 | 510 | 0.2729 | 0.9451 | 0.9449 |
| 0.0135 | 6.0 | 612 | 0.2811 | 0.9560 | 0.9562 |
| 0.0095 | 7.0 | 714 | 0.3160 | 0.9560 | 0.9562 |
| 0.001 | 8.0 | 816 | 0.3634 | 0.9396 | 0.9391 |
| 0.0002 | 9.0 | 918 | 0.3509 | 0.9451 | 0.9449 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for elidle/indobert-clean-post-training-fin-sa-1
Base model
indobenchmark/indobert-base-p1 Finetuned
elidle/indobert-fin_news-mlm