metadata
library_name: transformers
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
results: []
results
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: 0.0452
- Accuracy: 0.9861
- F1: 0.9854
- Precision: 0.9837
- Recall: 0.9872
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|---|---|---|
| 0.0371 | 1.0 | 739 | 0.0493 | 0.9875 | 0.9869 | 0.9851 | 0.9886 |
| 0.0407 | 2.0 | 1478 | 0.0432 | 0.9868 | 0.9862 | 0.9830 | 0.9893 |
| 0.0446 | 3.0 | 2217 | 0.0647 | 0.9841 | 0.9835 | 0.9735 | 0.9936 |
| 0.031 | 4.0 | 2956 | 0.0766 | 0.9854 | 0.9846 | 0.9892 | 0.9801 |
| 0.0072 | 5.0 | 3695 | 0.0816 | 0.9871 | 0.9865 | 0.9865 | 0.9865 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1
- Datasets 2.19.2
- Tokenizers 0.20.1