metadata
license: mit
base_model: indobenchmark/indobert-base-p2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: topic_model
results: []
topic_model
This model is a fine-tuned version of indobenchmark/indobert-base-p2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0145
- Accuracy: 0.9984
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 308 | 0.0315 | 0.9919 |
| 0.1039 | 2.0 | 616 | 0.0117 | 0.9984 |
| 0.1039 | 3.0 | 924 | 0.0147 | 0.9984 |
| 0.0047 | 4.0 | 1232 | 0.0223 | 0.9968 |
| 0.0002 | 5.0 | 1540 | 0.0138 | 0.9984 |
| 0.0002 | 6.0 | 1848 | 0.0140 | 0.9984 |
| 0.0001 | 7.0 | 2156 | 0.0142 | 0.9984 |
| 0.0001 | 8.0 | 2464 | 0.0144 | 0.9984 |
| 0.0001 | 9.0 | 2772 | 0.0145 | 0.9984 |
| 0.0001 | 10.0 | 3080 | 0.0145 | 0.9984 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0