sentiment-lora-r16a2d0.1-0
This model is a fine-tuned version of indolem/indobert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2912
- Accuracy: 0.8647
- Precision: 0.8346
- Recall: 0.8442
- F1: 0.8391
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: 30
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.559 | 1.0 | 122 | 0.5023 | 0.7268 | 0.6671 | 0.6592 | 0.6627 |
0.4818 | 2.0 | 244 | 0.4518 | 0.7569 | 0.7248 | 0.7605 | 0.7318 |
0.4129 | 3.0 | 366 | 0.3967 | 0.8246 | 0.7876 | 0.7959 | 0.7914 |
0.3519 | 4.0 | 488 | 0.3626 | 0.8496 | 0.8193 | 0.8161 | 0.8177 |
0.3191 | 5.0 | 610 | 0.3720 | 0.8471 | 0.8130 | 0.8393 | 0.8235 |
0.2977 | 6.0 | 732 | 0.3482 | 0.8546 | 0.8216 | 0.8422 | 0.8303 |
0.2861 | 7.0 | 854 | 0.3343 | 0.8672 | 0.8363 | 0.8535 | 0.8439 |
0.2662 | 8.0 | 976 | 0.3213 | 0.8622 | 0.8314 | 0.8425 | 0.8365 |
0.2618 | 9.0 | 1098 | 0.3246 | 0.8697 | 0.8399 | 0.8528 | 0.8458 |
0.2556 | 10.0 | 1220 | 0.3065 | 0.8596 | 0.8307 | 0.8307 | 0.8307 |
0.2353 | 11.0 | 1342 | 0.3148 | 0.8722 | 0.8416 | 0.8621 | 0.8505 |
0.24 | 12.0 | 1464 | 0.3098 | 0.8747 | 0.8451 | 0.8613 | 0.8524 |
0.2346 | 13.0 | 1586 | 0.2989 | 0.8772 | 0.8524 | 0.8506 | 0.8515 |
0.2367 | 14.0 | 1708 | 0.3001 | 0.8697 | 0.8399 | 0.8528 | 0.8458 |
0.2248 | 15.0 | 1830 | 0.3040 | 0.8722 | 0.8420 | 0.8596 | 0.8498 |
0.2174 | 16.0 | 1952 | 0.3016 | 0.8697 | 0.8386 | 0.8603 | 0.8479 |
0.2112 | 17.0 | 2074 | 0.2887 | 0.8647 | 0.8346 | 0.8442 | 0.8391 |
0.2162 | 18.0 | 2196 | 0.2980 | 0.8722 | 0.8416 | 0.8621 | 0.8505 |
0.2124 | 19.0 | 2318 | 0.2892 | 0.8697 | 0.8411 | 0.8478 | 0.8443 |
0.2118 | 20.0 | 2440 | 0.2912 | 0.8647 | 0.8346 | 0.8442 | 0.8391 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2
Model tree for apwic/sentiment-lora-r16a2d0.1-0
Base model
indolem/indobert-base-uncased
Finetuned
this model