---
base_model: bert-base-chinese
tags:
- generated_from_keras_callback
model-index:
- name: Hzmin9/my_awesome_model
  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. -->

# Hzmin9/my_awesome_model

This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1928
- Train Accuracy: 0.6725
- Validation Loss: 1.3273
- Validation Accuracy: 0.6725
- Epoch: 9

## 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': 'Adam', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2250, '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}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 2.0541     | 0.595          | 1.5183          | 0.5950              | 0     |
| 1.3021     | 0.6125         | 1.2977          | 0.6125              | 1     |
| 0.9285     | 0.6625         | 1.2059          | 0.6625              | 2     |
| 0.7071     | 0.6625         | 1.1796          | 0.6625              | 3     |
| 0.5354     | 0.6525         | 1.2179          | 0.6525              | 4     |
| 0.4165     | 0.6825         | 1.1801          | 0.6825              | 5     |
| 0.3302     | 0.6675         | 1.3224          | 0.6675              | 6     |
| 0.2655     | 0.6725         | 1.3056          | 0.6725              | 7     |
| 0.2195     | 0.6675         | 1.3366          | 0.6675              | 8     |
| 0.1928     | 0.6725         | 1.3273          | 0.6725              | 9     |


### Framework versions

- Transformers 4.33.0
- TensorFlow 2.13.0
- Datasets 2.14.4
- Tokenizers 0.13.3