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---
tags:
- generated_from_keras_callback
model-index:
- name: aadhistii/tsel-finetune-indobert-base-p1-formal-v1
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-indobert-base-p1-formal-v1
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0058
- Validation Loss: 1.0176
- Train Precision: 0.7872
- Train Recall: 0.7872
- Train F1: 0.7872
- 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 940, '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 Precision | Train Recall | Train F1 | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:-----:|
| 0.8278 | 0.6154 | 0.7447 | 0.7447 | 0.7447 | 0 |
| 0.5217 | 0.5614 | 0.7872 | 0.7872 | 0.7872 | 1 |
| 0.2524 | 0.6063 | 0.7394 | 0.7394 | 0.7394 | 2 |
| 0.0923 | 0.8341 | 0.7660 | 0.7660 | 0.7660 | 3 |
| 0.0524 | 0.9632 | 0.7261 | 0.7261 | 0.7261 | 4 |
| 0.0215 | 0.9419 | 0.7819 | 0.7819 | 0.7819 | 5 |
| 0.0174 | 1.0431 | 0.7553 | 0.7553 | 0.7553 | 6 |
| 0.0108 | 1.0288 | 0.75 | 0.75 | 0.75 | 7 |
| 0.0087 | 1.0092 | 0.7846 | 0.7846 | 0.7846 | 8 |
| 0.0058 | 1.0176 | 0.7872 | 0.7872 | 0.7872 | 9 |
### Framework versions
- Transformers 4.42.3
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1
|