---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: tunarebus/distilbert-base-uncased-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/distilbert-base-uncased-finetuned-tweet_pemilu2024

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 2.5045
- Validation Loss: 2.4250
- Epoch: 24

## 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': -931, '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 |
|:----------:|:---------------:|:-----:|
| 4.9932     | 4.6882          | 0     |
| 4.6678     | 4.3954          | 1     |
| 4.4076     | 4.1306          | 2     |
| 4.1610     | 3.8876          | 3     |
| 3.9036     | 3.6392          | 4     |
| 3.6549     | 3.4398          | 5     |
| 3.4439     | 3.2595          | 6     |
| 3.3055     | 3.0760          | 7     |
| 3.1307     | 2.8918          | 8     |
| 2.9749     | 2.8005          | 9     |
| 2.8441     | 2.7331          | 10    |
| 2.7790     | 2.6070          | 11    |
| 2.6932     | 2.5804          | 12    |
| 2.6181     | 2.4717          | 13    |
| 2.5241     | 2.4091          | 14    |
| 2.4900     | 2.4074          | 15    |
| 2.5065     | 2.4340          | 16    |
| 2.4976     | 2.4425          | 17    |
| 2.4894     | 2.4307          | 18    |
| 2.5294     | 2.4356          | 19    |
| 2.4649     | 2.4002          | 20    |
| 2.5011     | 2.4172          | 21    |
| 2.5083     | 2.4533          | 22    |
| 2.4822     | 2.4224          | 23    |
| 2.5045     | 2.4250          | 24    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.15.0
- Tokenizers 0.15.0