metadata
library_name: transformers
license: mit
base_model: indobenchmark/indobert-large-p2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results_indobert-large-p2_preprocessing_tuning
results: []
results_indobert-large-p2_preprocessing_tuning
This model is a fine-tuned version of indobenchmark/indobert-large-p2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2148
- Accuracy: 0.5659
- Precision: 0.6035
- Recall: 0.5365
- F1: 0.5245
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: 6.859942542315833e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.5861 | 1.0 | 111 | 1.5168 | 0.3591 | 0.4502 | 0.2992 | 0.2327 |
| 1.5187 | 2.0 | 222 | 1.4637 | 0.4091 | 0.4136 | 0.3625 | 0.3418 |
| 1.4643 | 3.0 | 333 | 1.4239 | 0.4591 | 0.4841 | 0.4226 | 0.3973 |
| 1.4121 | 4.0 | 444 | 1.3840 | 0.4932 | 0.5254 | 0.4505 | 0.4407 |
| 1.3867 | 5.0 | 555 | 1.3513 | 0.5 | 0.4415 | 0.4569 | 0.4354 |
| 1.354 | 6.0 | 666 | 1.3264 | 0.5273 | 0.5355 | 0.4904 | 0.4677 |
| 1.3291 | 7.0 | 777 | 1.3046 | 0.5295 | 0.5774 | 0.4884 | 0.4707 |
| 1.305 | 8.0 | 888 | 1.2889 | 0.5364 | 0.5420 | 0.5069 | 0.5010 |
| 1.2878 | 9.0 | 999 | 1.2736 | 0.525 | 0.5651 | 0.4960 | 0.4928 |
| 1.2766 | 10.0 | 1110 | 1.2594 | 0.5432 | 0.5880 | 0.5045 | 0.4849 |
| 1.2655 | 11.0 | 1221 | 1.2490 | 0.55 | 0.5661 | 0.5142 | 0.4887 |
| 1.2462 | 12.0 | 1332 | 1.2384 | 0.55 | 0.5832 | 0.5171 | 0.5025 |
| 1.2385 | 13.0 | 1443 | 1.2321 | 0.5386 | 0.5710 | 0.4972 | 0.4901 |
| 1.23 | 14.0 | 1554 | 1.2251 | 0.55 | 0.5910 | 0.5181 | 0.5060 |
| 1.2292 | 15.0 | 1665 | 1.2196 | 0.5545 | 0.5709 | 0.5256 | 0.5155 |
| 1.2246 | 16.0 | 1776 | 1.2148 | 0.5659 | 0.6035 | 0.5365 | 0.5245 |
| 1.2229 | 17.0 | 1887 | 1.2113 | 0.5659 | 0.6022 | 0.5366 | 0.5260 |
| 1.2235 | 18.0 | 1998 | 1.2093 | 0.5614 | 0.5960 | 0.5327 | 0.5211 |
| 1.2125 | 19.0 | 2109 | 1.2079 | 0.5614 | 0.5954 | 0.5329 | 0.5217 |
| 1.2153 | 20.0 | 2220 | 1.2074 | 0.5591 | 0.5929 | 0.5307 | 0.5194 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2