metadata
license: mit
base_model: indobenchmark/indobert-large-p2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: indonli-indobert-large
results: []
indonli-indobert-large
This model is a fine-tuned version of indobenchmark/indobert-large-p2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9753
- Accuracy: 0.6350
- Precision: 0.6350
- Recall: 0.6350
- F1 Score: 0.6362
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: 3e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 101
- 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 | Precision | Recall | F1 Score |
|---|---|---|---|---|---|---|---|
| 1.0324 | 1.0 | 2583 | 0.9492 | 0.5508 | 0.5508 | 0.5508 | 0.5172 |
| 0.9234 | 2.0 | 5166 | 0.8837 | 0.6099 | 0.6099 | 0.6099 | 0.6106 |
| 0.8318 | 3.0 | 7749 | 0.8718 | 0.6277 | 0.6277 | 0.6277 | 0.6302 |
| 0.7417 | 4.0 | 10332 | 0.9005 | 0.6313 | 0.6313 | 0.6313 | 0.6326 |
| 0.6788 | 5.0 | 12915 | 0.9380 | 0.6368 | 0.6368 | 0.6368 | 0.6381 |
| 0.6263 | 6.0 | 15498 | 0.9753 | 0.6350 | 0.6350 | 0.6350 | 0.6362 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3