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---
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
|