metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bdc2024-indobert-2
results: []
bdc2024-indobert-2
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5554
- Accuracy: 0.9331
- Balanced Accuracy: 0.8724
- Precision: 0.9353
- Recall: 0.9331
- F1: 0.9289
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 | 483 | 0.5108 | 0.9197 | 0.8454 | 0.9195 | 0.9197 | 0.9132 |
0.0773 | 2.0 | 966 | 0.5374 | 0.9235 | 0.8668 | 0.9266 | 0.9235 | 0.9196 |
0.0374 | 3.0 | 1449 | 0.5451 | 0.9331 | 0.8689 | 0.9359 | 0.9331 | 0.9281 |
0.0242 | 4.0 | 1932 | 0.5567 | 0.9331 | 0.8726 | 0.9353 | 0.9331 | 0.9288 |
0.0162 | 5.0 | 2415 | 0.5554 | 0.9331 | 0.8724 | 0.9353 | 0.9331 | 0.9289 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.13.3