---
library_name: transformers
base_model: bert-base-chinese
tags:
- generated_from_keras_callback
model-index:
- name: node-py/my_awesome_eli5_clm-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. -->

# node-py/my_awesome_eli5_clm-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: 0.0530
- Epoch: 34

## 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': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Epoch |
|:----------:|:-----:|
| 0.0882     | 0     |
| 0.0878     | 1     |
| 0.0852     | 2     |
| 0.0824     | 3     |
| 0.0810     | 4     |
| 0.0812     | 5     |
| 0.0790     | 6     |
| 0.0772     | 7     |
| 0.0755     | 8     |
| 0.0749     | 9     |
| 0.0717     | 10    |
| 0.0722     | 11    |
| 0.0718     | 12    |
| 0.0689     | 13    |
| 0.0863     | 14    |
| 0.0838     | 15    |
| 0.0731     | 16    |
| 0.0768     | 17    |
| 0.0675     | 18    |
| 0.0646     | 19    |
| 0.0650     | 20    |
| 0.0627     | 21    |
| 0.0610     | 22    |
| 0.0594     | 23    |
| 0.0585     | 24    |
| 0.0585     | 25    |
| 0.0577     | 26    |
| 0.0569     | 27    |
| 0.0565     | 28    |
| 0.0542     | 29    |
| 0.0531     | 30    |
| 0.0531     | 31    |
| 0.0532     | 32    |
| 0.0535     | 33    |
| 0.0530     | 34    |


### Framework versions

- Transformers 4.44.2
- TensorFlow 2.17.0
- Datasets 2.21.0
- Tokenizers 0.19.1