---
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