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---
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
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
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: 6.8798
- Validation Loss: 6.6169
- Epoch: 8
## 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 |
|:----------:|:---------------:|:-----:|
| 11.7870 | 11.4348 | 0 |
| 10.8383 | 10.1366 | 1 |
| 9.6098 | 9.0621 | 2 |
| 8.7602 | 8.2954 | 3 |
| 8.0949 | 7.7276 | 4 |
| 7.6334 | 7.2756 | 5 |
| 7.3192 | 7.0363 | 6 |
| 7.1297 | 6.8447 | 7 |
| 6.8798 | 6.6169 | 8 |
### Framework versions
- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.0
- Tokenizers 0.15.0
|