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---
license: mit
base_model: ilos-vigil/bigbird-small-indonesian
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test_trainer
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# test_trainer
This model is a fine-tuned version of [ilos-vigil/bigbird-small-indonesian](https://huggingface.co/ilos-vigil/bigbird-small-indonesian) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2500
- Accuracy: 0.5
## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2611 | 0.04 | 500 | 0.2617 | 0.5 |
| 0.2547 | 0.07 | 1000 | 0.2525 | 0.5 |
| 0.2527 | 0.11 | 1500 | 0.2500 | 0.5 |
| 0.2523 | 0.14 | 2000 | 0.2522 | 0.5 |
| 0.253 | 0.18 | 2500 | 0.2504 | 0.5 |
| 0.252 | 0.21 | 3000 | 0.2553 | 0.5 |
| 0.2662 | 0.25 | 3500 | 0.2501 | 0.5 |
| 0.2869 | 0.29 | 4000 | 0.2705 | 0.5 |
| 0.2534 | 0.32 | 4500 | 0.2505 | 0.5 |
| 0.252 | 0.36 | 5000 | 0.2504 | 0.5 |
| 0.2518 | 0.39 | 5500 | 0.2526 | 0.5 |
| 0.2508 | 0.43 | 6000 | 0.2501 | 0.5 |
| 0.2512 | 0.46 | 6500 | 0.2501 | 0.5 |
| 0.251 | 0.5 | 7000 | 0.2500 | 0.5 |
| 0.2502 | 0.54 | 7500 | 0.2502 | 0.5 |
| 0.2507 | 0.57 | 8000 | 0.2545 | 0.5 |
| 0.2511 | 0.61 | 8500 | 0.2509 | 0.5 |
| 0.2503 | 0.64 | 9000 | 0.2500 | 0.5 |
| 0.2506 | 0.68 | 9500 | 0.2501 | 0.5 |
| 0.2505 | 0.71 | 10000 | 0.2504 | 0.5 |
| 0.2505 | 0.75 | 10500 | 0.2504 | 0.5 |
| 0.2504 | 0.79 | 11000 | 0.2501 | 0.5 |
| 0.2502 | 0.82 | 11500 | 0.2500 | 0.5 |
| 0.2503 | 0.86 | 12000 | 0.2500 | 0.5 |
| 0.2501 | 0.89 | 12500 | 0.2500 | 0.5 |
| 0.2503 | 0.93 | 13000 | 0.2500 | 0.5 |
| 0.2502 | 0.96 | 13500 | 0.2500 | 0.5 |
| 0.2502 | 1.0 | 14000 | 0.2500 | 0.5 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1
- Datasets 2.15.0
- Tokenizers 0.15.0
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