metadata
license: mit
base_model: indobenchmark/indobart
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bdc2024-indobart-gpt-aug
results: []
bdc2024-indobart-gpt-aug
This model is a fine-tuned version of indobenchmark/indobart on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4480
- Accuracy: 0.9273
- Balanced Accuracy: 0.8560
- Precision: 0.9296
- Recall: 0.9273
- F1: 0.9205
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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Balanced Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 483 | 0.7053 | 0.7820 | 0.5122 | 0.7407 | 0.7820 | 0.7499 |
| 0.8051 | 2.0 | 966 | 0.5075 | 0.8757 | 0.6954 | 0.8779 | 0.8757 | 0.8622 |
| 0.4597 | 3.0 | 1449 | 0.4041 | 0.9197 | 0.8361 | 0.9198 | 0.9197 | 0.9122 |
| 0.2475 | 4.0 | 1932 | 0.4224 | 0.9254 | 0.8626 | 0.9255 | 0.9254 | 0.9202 |
| 0.1303 | 5.0 | 2415 | 0.4438 | 0.9273 | 0.8559 | 0.9295 | 0.9273 | 0.9214 |
| 0.0771 | 6.0 | 2898 | 0.4480 | 0.9273 | 0.8560 | 0.9296 | 0.9273 | 0.9205 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.13.3