---
base_model: bert-base-chinese
tags:
- generated_from_keras_callback
model-index:
- name: AIYIYA/my_12
  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. -->

# AIYIYA/my_12

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: 0.5441
- Validation Loss: 1.0817
- Train Accuracy: 0.7799
- Epoch: 11

## 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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 580, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 3.3278     | 2.9680          | 0.3208         | 0     |
| 2.7007     | 2.5022          | 0.4654         | 1     |
| 2.1853     | 2.0269          | 0.5597         | 2     |
| 1.7380     | 1.7066          | 0.6352         | 3     |
| 1.4422     | 1.5095          | 0.6855         | 4     |
| 1.1789     | 1.3789          | 0.7484         | 5     |
| 1.0105     | 1.3038          | 0.7484         | 6     |
| 0.8728     | 1.2295          | 0.7484         | 7     |
| 0.7790     | 1.1804          | 0.7484         | 8     |
| 0.6699     | 1.1553          | 0.7673         | 9     |
| 0.6131     | 1.1061          | 0.7673         | 10    |
| 0.5441     | 1.0817          | 0.7799         | 11    |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.13.1
- Tokenizers 0.13.3