metadata
license: mit
base_model: indobenchmark/indobert-base-p2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: sentiment_model
results: []
sentiment_model
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: 0.1665
- Accuracy: 0.9720
- F1: 0.9259
- Precision: 0.9615
- Recall: 0.8929
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 | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 72 | 0.2060 | 0.9510 | 0.8727 | 0.8889 | 0.8571 |
| No log | 2.0 | 144 | 0.2337 | 0.9580 | 0.8846 | 0.9583 | 0.8214 |
| No log | 3.0 | 216 | 0.2416 | 0.9441 | 0.8571 | 0.8571 | 0.8571 |
| No log | 4.0 | 288 | 0.1905 | 0.9580 | 0.8846 | 0.9583 | 0.8214 |
| No log | 5.0 | 360 | 0.2029 | 0.9580 | 0.8929 | 0.8929 | 0.8929 |
| No log | 6.0 | 432 | 0.1665 | 0.9720 | 0.9259 | 0.9615 | 0.8929 |
| 0.0706 | 7.0 | 504 | 0.1899 | 0.9580 | 0.8889 | 0.9231 | 0.8571 |
| 0.0706 | 8.0 | 576 | 0.1990 | 0.9580 | 0.8889 | 0.9231 | 0.8571 |
| 0.0706 | 9.0 | 648 | 0.2139 | 0.9580 | 0.8889 | 0.9231 | 0.8571 |
| 0.0706 | 10.0 | 720 | 0.2171 | 0.9580 | 0.8889 | 0.9231 | 0.8571 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0