indobert-base-p2-finetuned-mer-80k
This model is a fine-tuned version of indobenchmark/indobert-base-p2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4680
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.9647 | 1.0 | 2305 | 2.1419 |
| 2.0987 | 2.0 | 4610 | 1.8580 |
| 1.8866 | 3.0 | 6915 | 1.7170 |
| 1.7696 | 4.0 | 9220 | 1.6357 |
| 1.6951 | 5.0 | 11525 | 1.5761 |
| 1.6383 | 6.0 | 13830 | 1.5354 |
| 1.599 | 7.0 | 16135 | 1.5074 |
| 1.5738 | 8.0 | 18440 | 1.4862 |
| 1.5516 | 9.0 | 20745 | 1.4700 |
| 1.5382 | 10.0 | 23050 | 1.4633 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.7.0
- Tokenizers 0.13.2