metadata
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: indobert_artha
results: []
indobert_artha
This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6470
- Balanced accuracy: 0.4809
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Balanced accuracy |
|---|---|---|---|---|
| 1.4443 | 1.0 | 92 | 1.2032 | 0.125 |
| 1.112 | 2.0 | 184 | 0.9012 | 0.3006 |
| 0.8258 | 3.0 | 276 | 0.8611 | 0.4565 |
| 0.6286 | 4.0 | 368 | 0.7711 | 0.4397 |
| 0.4205 | 5.0 | 460 | 0.8665 | 0.4900 |
| 0.3025 | 6.0 | 552 | 0.9085 | 0.4572 |
| 0.1904 | 7.0 | 644 | 1.1407 | 0.4584 |
| 0.1387 | 8.0 | 736 | 1.2191 | 0.4682 |
| 0.1294 | 9.0 | 828 | 1.3164 | 0.4470 |
| 0.097 | 10.0 | 920 | 1.4438 | 0.4245 |
| 0.0843 | 11.0 | 1012 | 1.3584 | 0.4603 |
| 0.0829 | 12.0 | 1104 | 1.3619 | 0.4442 |
| 0.0667 | 13.0 | 1196 | 1.4805 | 0.4536 |
| 0.0596 | 14.0 | 1288 | 1.6224 | 0.4917 |
| 0.0538 | 15.0 | 1380 | 1.6581 | 0.4253 |
| 0.0488 | 16.0 | 1472 | 1.6128 | 0.4982 |
| 0.0442 | 17.0 | 1564 | 1.8136 | 0.4951 |
| 0.0426 | 18.0 | 1656 | 1.6496 | 0.4859 |
| 0.0384 | 19.0 | 1748 | 1.6517 | 0.4702 |
| 0.0311 | 20.0 | 1840 | 1.6183 | 0.4901 |
| 0.0288 | 21.0 | 1932 | 1.7072 | 0.4647 |
| 0.0283 | 22.0 | 2024 | 1.6827 | 0.4653 |
| 0.0244 | 23.0 | 2116 | 1.6211 | 0.4777 |
| 0.0264 | 24.0 | 2208 | 1.6428 | 0.4719 |
| 0.0202 | 25.0 | 2300 | 1.6462 | 0.4907 |
| 0.0198 | 26.0 | 2392 | 1.6719 | 0.4841 |
| 0.024 | 27.0 | 2484 | 1.6376 | 0.4957 |
| 0.0205 | 28.0 | 2576 | 1.6477 | 0.4775 |
| 0.0162 | 29.0 | 2668 | 1.6459 | 0.4909 |
| 0.0165 | 30.0 | 2760 | 1.6470 | 0.4809 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1