---
library_name: transformers
license: cc-by-sa-4.0
base_model: klue/bert-base
tags:
- generated_from_keras_callback
model-index:
- name: bert-base-nsmc
  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. -->

# bert-base-nsmc

This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0288
- Train Accuracy: 0.9914
- Validation Loss: 0.5336
- Validation Accuracy: 0.8714
- Epoch: 4

## 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': 5e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 1058, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 117, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': np.float32(0.9), 'beta_2': np.float32(0.999), 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.1}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.3967     | 0.8134         | 0.3805          | 0.8266              | 0     |
| 0.2183     | 0.9149         | 0.3068          | 0.8740              | 1     |
| 0.1075     | 0.9622         | 0.4280          | 0.8696              | 2     |
| 0.0481     | 0.9843         | 0.4970          | 0.8722              | 3     |
| 0.0288     | 0.9914         | 0.5336          | 0.8714              | 4     |


### Framework versions

- Transformers 4.55.2
- TensorFlow 2.19.0
- Datasets 4.0.0
- Tokenizers 0.21.4