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---
license: mit
base_model: ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa
tags:
- generated_from_keras_callback
model-index:
- name: aadhistii/tsel-finetune-bert-base-indonesian-1.5G-sentiment-analysis-smsa
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. -->
# aadhistii/tsel-finetune-bert-base-indonesian-1.5G-sentiment-analysis-smsa
This model is a fine-tuned version of [ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa](https://huggingface.co/ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0481
- Validation Loss: 1.3972
- Train Accuracy: 0.6541
- Epoch: 6
## 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 730, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 1.3087 | 0.8960 | 0.6336 | 0 |
| 0.7406 | 0.9109 | 0.6199 | 1 |
| 0.5737 | 0.8554 | 0.6473 | 2 |
| 0.3301 | 0.9670 | 0.6473 | 3 |
| 0.1785 | 1.0983 | 0.6712 | 4 |
| 0.0729 | 1.2668 | 0.6678 | 5 |
| 0.0481 | 1.3972 | 0.6541 | 6 |
### Framework versions
- Transformers 4.42.3
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1
|