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license: apache-2.0
base_model: indolem/indobertweet-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: damand2061/innermore-x-indobertweet-base-uncased
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. -->
# damand2061/innermore-x-indobertweet-base-uncased
This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0022
- Validation Loss: 0.1782
- Train Precision: 0.8152
- Train Recall: 0.7350
- Train F1: 0.7730
- Train Accuracy: 0.9629
- Epoch: 14
## 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': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0002, 'decay_steps': 420, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 0.5919 | 0.3227 | 0.6263 | 0.2650 | 0.3724 | 0.9078 | 0 |
| 0.2379 | 0.1878 | 0.6948 | 0.6325 | 0.6622 | 0.9434 | 1 |
| 0.1314 | 0.1674 | 0.6711 | 0.6453 | 0.6580 | 0.9477 | 2 |
| 0.0852 | 0.1958 | 0.6562 | 0.7179 | 0.6857 | 0.9425 | 3 |
| 0.0506 | 0.1677 | 0.7907 | 0.7265 | 0.7572 | 0.9539 | 4 |
| 0.0239 | 0.1493 | 0.7689 | 0.7393 | 0.7538 | 0.9615 | 5 |
| 0.0194 | 0.1679 | 0.8102 | 0.7479 | 0.7778 | 0.9610 | 6 |
| 0.0122 | 0.1739 | 0.7328 | 0.7265 | 0.7296 | 0.9563 | 7 |
| 0.0084 | 0.2116 | 0.8118 | 0.6453 | 0.7190 | 0.9539 | 8 |
| 0.0059 | 0.1724 | 0.8 | 0.7179 | 0.7568 | 0.9591 | 9 |
| 0.0037 | 0.1744 | 0.7972 | 0.7222 | 0.7578 | 0.9601 | 10 |
| 0.0029 | 0.1771 | 0.7981 | 0.7265 | 0.7606 | 0.9601 | 11 |
| 0.0020 | 0.1769 | 0.8047 | 0.7393 | 0.7706 | 0.9620 | 12 |
| 0.0020 | 0.1773 | 0.8152 | 0.7350 | 0.7730 | 0.9629 | 13 |
| 0.0022 | 0.1782 | 0.8152 | 0.7350 | 0.7730 | 0.9629 | 14 |
### Framework versions
- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2
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