---
base_model: bert-base-chinese
tags:
- generated_from_keras_callback
model-index:
- name: imagine0711/bert-base-chinese-finetuned-tcfd
  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. -->

# imagine0711/bert-base-chinese-finetuned-tcfd

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: 0.6361
- Train Accuracy: 0.0595
- Validation Loss: 0.6676
- Validation Accuracy: 0.0605
- Epoch: 7

## 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': -800, '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: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.9501     | 0.0559         | 0.8560          | 0.0569              | 0     |
| 0.8356     | 0.0571         | 0.7513          | 0.0585              | 1     |
| 0.7771     | 0.0584         | 0.7556          | 0.0602              | 2     |
| 0.6974     | 0.0590         | 0.6988          | 0.0589              | 3     |
| 0.6641     | 0.0599         | 0.5843          | 0.0609              | 4     |
| 0.6423     | 0.0599         | 0.6116          | 0.0605              | 5     |
| 0.6540     | 0.0596         | 0.6470          | 0.0605              | 6     |
| 0.6361     | 0.0595         | 0.6676          | 0.0605              | 7     |


### Framework versions

- Transformers 4.41.1
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1