---
base_model: bert-base-chinese
tags:
- generated_from_keras_callback
model-index:
- name: Mattis0525/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. -->

# Mattis0525/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: 0.6479
- Train Accuracy: 0.0596
- Validation Loss: 0.6639
- Validation Accuracy: 0.0602
- Epoch: 5

## 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 |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.9480     | 0.0555         | 0.8742          | 0.0566              | 0     |
| 0.8735     | 0.0567         | 0.7660          | 0.0589              | 1     |
| 0.7694     | 0.0574         | 0.7093          | 0.0584              | 2     |
| 0.7190     | 0.0588         | 0.6563          | 0.0604              | 3     |
| 0.6720     | 0.0592         | 0.6636          | 0.0601              | 4     |
| 0.6479     | 0.0596         | 0.6639          | 0.0602              | 5     |


### Framework versions

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