---
license: mit
base_model: w11wo/indonesian-roberta-base-posp-tagger
tags:
- generated_from_keras_callback
model-index:
- name: freyagracia/indonesian-roberta-base-posp-tagger-finetuned-tweet_pemilu_postagger_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. -->

# freyagracia/indonesian-roberta-base-posp-tagger-finetuned-tweet_pemilu_postagger_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: 7.6422
- Validation Loss: 7.3402
- Epoch: 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:
- 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 |
|:----------:|:---------------:|:-----:|
| 12.0302    | 11.6101         | 0     |
| 11.0135    | 10.3624         | 1     |
| 9.7682     | 9.2346          | 2     |
| 8.8465     | 8.2572          | 3     |
| 8.1298     | 7.7354          | 4     |
| 7.6422     | 7.3402          | 5     |


### Framework versions

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