---
license: mit
base_model: w11wo/indonesian-roberta-base-posp-tagger
tags:
- generated_from_keras_callback
model-index:
- name: tunarebus/indonesian-roberta-base-posp-tagger-finetuned-tweet_pemilu2024_2
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# tunarebus/indonesian-roberta-base-posp-tagger-finetuned-tweet_pemilu2024_2

This model is a fine-tuned version of [w11wo/indonesian-roberta-base-posp-tagger](https://huggingface.co/w11wo/indonesian-roberta-base-posp-tagger) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 6.7581
- Validation Loss: 6.4974
- Epoch: 9

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -969, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 11.7200    | 11.3464         | 0     |
| 10.7101    | 10.0138         | 1     |
| 9.4860     | 9.0052          | 2     |
| 8.6505     | 8.1202          | 3     |
| 8.0255     | 7.6902          | 4     |
| 7.6350     | 7.2934          | 5     |
| 7.3084     | 7.0449          | 6     |
| 7.0715     | 6.9226          | 7     |
| 6.9394     | 6.6571          | 8     |
| 6.7581     | 6.4974          | 9     |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.0
- Tokenizers 0.15.0