<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
indobert-base-p2-finetuned-mer-10k
This model is a fine-tuned version of indobenchmark/indobert-base-p2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3370
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 |
|---|---|---|---|
| 4.9568 | 1.0 | 274 | 3.6237 |
| 3.4802 | 2.0 | 548 | 3.0803 |
| 3.0626 | 3.0 | 822 | 2.8108 |
| 2.8591 | 4.0 | 1096 | 2.6345 |
| 2.7182 | 5.0 | 1370 | 2.5492 |
| 2.6223 | 6.0 | 1644 | 2.4692 |
| 2.5426 | 7.0 | 1918 | 2.4122 |
| 2.5019 | 8.0 | 2192 | 2.3611 |
| 2.4649 | 9.0 | 2466 | 2.3447 |
| 2.4631 | 10.0 | 2740 | 2.3392 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Tokenizers 0.13.2
