metadata
license: mit
base_model: indobenchmark/indobart
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bdc2024-indobert-filtered-1
results: []
bdc2024-indobert-filtered-1
This model is a fine-tuned version of indobenchmark/indobart on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5705
- Accuracy: 0.8317
- Balanced Accuracy: 0.6247
- Precision: 0.8316
- Recall: 0.8317
- F1: 0.8173
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: 1e-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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Balanced Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 298 | 0.9280 | 0.6998 | 0.3859 | 0.6874 | 0.6998 | 0.6350 |
| 0.886 | 2.0 | 596 | 0.7598 | 0.7648 | 0.4862 | 0.7263 | 0.7648 | 0.7251 |
| 0.886 | 3.0 | 894 | 0.6400 | 0.7992 | 0.5757 | 0.8018 | 0.7992 | 0.7772 |
| 0.5453 | 4.0 | 1192 | 0.5738 | 0.8298 | 0.6337 | 0.8321 | 0.8298 | 0.8184 |
| 0.5453 | 5.0 | 1490 | 0.5705 | 0.8317 | 0.6247 | 0.8316 | 0.8317 | 0.8173 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3