metadata
license: mit
base_model: indobenchmark/indobert-base-p2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: fitur_model
results: []
fitur_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: 0.4122
- Accuracy: 0.8077
- F1: 0.8789
- Precision: 0.8355
- Recall: 0.9270
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 | 92 | 0.4122 | 0.8077 | 0.8789 | 0.8355 | 0.9270 |
| No log | 2.0 | 184 | 0.4881 | 0.8022 | 0.8657 | 0.8855 | 0.8467 |
| No log | 3.0 | 276 | 0.6448 | 0.8297 | 0.8912 | 0.8581 | 0.9270 |
| No log | 4.0 | 368 | 0.8912 | 0.8132 | 0.8786 | 0.8601 | 0.8978 |
| No log | 5.0 | 460 | 1.2147 | 0.7967 | 0.8702 | 0.8378 | 0.9051 |
| 0.1904 | 6.0 | 552 | 1.3269 | 0.8077 | 0.8754 | 0.8542 | 0.8978 |
| 0.1904 | 7.0 | 644 | 1.4276 | 0.7967 | 0.8693 | 0.8425 | 0.8978 |
| 0.1904 | 8.0 | 736 | 1.4681 | 0.8022 | 0.8732 | 0.8435 | 0.9051 |
| 0.1904 | 9.0 | 828 | 1.4804 | 0.7967 | 0.8693 | 0.8425 | 0.8978 |
| 0.1904 | 10.0 | 920 | 1.4867 | 0.8022 | 0.8732 | 0.8435 | 0.9051 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0