metadata
library_name: transformers
license: mit
base_model: indobenchmark/indobert-large-p1
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results_indobert_emotion
results: []
results_indobert_emotion
This model is a fine-tuned version of indobenchmark/indobert-large-p1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7407
- Accuracy: 0.7682
- Precision: 0.7698
- Recall: 0.7773
- F1: 0.7668
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.6564 | 1.0 | 111 | 1.5223 | 0.2955 | 0.3507 | 0.2474 | 0.1849 |
| 1.3092 | 2.0 | 222 | 1.0048 | 0.6205 | 0.6162 | 0.6264 | 0.6064 |
| 0.8835 | 3.0 | 333 | 0.7088 | 0.75 | 0.7506 | 0.7557 | 0.7491 |
| 0.6384 | 4.0 | 444 | 0.7077 | 0.7477 | 0.7458 | 0.7658 | 0.7499 |
| 0.4962 | 5.0 | 555 | 0.7407 | 0.7682 | 0.7698 | 0.7773 | 0.7668 |
| 0.3875 | 6.0 | 666 | 0.7610 | 0.7477 | 0.7457 | 0.7649 | 0.7517 |
| 0.2849 | 7.0 | 777 | 0.8377 | 0.7523 | 0.7565 | 0.7598 | 0.7545 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1