metadata
license: mit
base_model: indobenchmark/indobert-lite-base-p1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: indobert-lite-base-p1-indonli-multilingual-nli-distil-mdeberta
results: []
indobert-lite-base-p1-indonli-multilingual-nli-distil-mdeberta
This model is a fine-tuned version of indobenchmark/indobert-lite-base-p1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5005
- Accuracy: 0.6545
- F1: 0.6524
- Precision: 0.6615
- Recall: 0.6577
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: 64
- eval_batch_size: 64
- 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 | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4808 | 1.0 | 1803 | 0.4418 | 0.7683 | 0.7593 | 0.7904 | 0.7554 |
| 0.4529 | 2.0 | 3606 | 0.4343 | 0.7738 | 0.7648 | 0.7893 | 0.7619 |
| 0.4263 | 3.0 | 5409 | 0.4383 | 0.7861 | 0.7828 | 0.7874 | 0.7807 |
| 0.398 | 4.0 | 7212 | 0.4456 | 0.7792 | 0.7767 | 0.7792 | 0.7756 |
| 0.3772 | 5.0 | 9015 | 0.4499 | 0.7711 | 0.7674 | 0.7700 | 0.7661 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0