transformers tf roberta fill-mask generated_from_keras_callback base_model:w11wo/indonesian-roberta-base-posp-tagger license:mit autotrain_compatible endpoints_compatible region:us
---
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-tweetdinastipolitik
  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-tweetdinastipolitik

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: 5.1186
- Validation Loss: 5.2613
- Epoch: 33

## 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: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'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': -980, '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': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 7.6412     | 7.4740          | 0     |
| 7.5082     | 7.3516          | 1     |
| 7.4002     | 7.2847          | 2     |
| 7.2814     | 7.1402          | 3     |
| 7.1623     | 6.9974          | 4     |
| 7.0393     | 6.9544          | 5     |
| 6.9725     | 6.8025          | 6     |
| 6.8398     | 6.7491          | 7     |
| 6.7369     | 6.6489          | 8     |
| 6.6285     | 6.5881          | 9     |
| 6.5252     | 6.4414          | 10    |
| 6.5094     | 6.3932          | 11    |
| 6.4500     | 6.2782          | 12    |
| 6.3615     | 6.2943          | 13    |
| 6.3066     | 6.2166          | 14    |
| 6.2139     | 6.1871          | 15    |
| 6.1785     | 6.1024          | 16    |
| 5.9922     | 6.0100          | 17    |
| 6.0045     | 6.0078          | 18    |
| 5.9443     | 5.9436          | 19    |
| 5.8311     | 5.8359          | 20    |
| 5.8252     | 5.8134          | 21    |
| 5.7629     | 5.7652          | 22    |
| 5.6416     | 5.7127          | 23    |
| 5.5541     | 5.6641          | 24    |
| 5.5813     | 5.5408          | 25    |
| 5.5254     | 5.6771          | 26    |
| 5.5086     | 5.5469          | 27    |
| 5.4037     | 5.5299          | 28    |
| 5.3488     | 5.4362          | 29    |
| 5.2641     | 5.3928          | 30    |
| 5.2668     | 5.3659          | 31    |
| 5.1900     | 5.3624          | 32    |
| 5.1186     | 5.2613          | 33    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.0
