metadata
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: indobert-finetuned-sentiment-happiness-index
results: []
indobert-finetuned-sentiment-happiness-index
This model is a fine-tuned version of indobenchmark/indobert-base-p1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4822
- Accuracy: 0.7983
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 270 | 0.5354 | 0.7835 |
| 0.532 | 2.0 | 540 | 0.6245 | 0.7567 |
| 0.532 | 3.0 | 810 | 0.7406 | 0.7826 |
| 0.1836 | 4.0 | 1080 | 1.0813 | 0.7919 |
| 0.1836 | 5.0 | 1350 | 1.2524 | 0.7891 |
| 0.0446 | 6.0 | 1620 | 1.3158 | 0.8039 |
| 0.0446 | 7.0 | 1890 | 1.4308 | 0.7965 |
| 0.0152 | 8.0 | 2160 | 1.4485 | 0.7974 |
| 0.0152 | 9.0 | 2430 | 1.4915 | 0.8030 |
| 0.0054 | 10.0 | 2700 | 1.4822 | 0.7983 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3