---
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: 0.3272
- Epoch: 64

## 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 |
|:----------:|:-----:|
| 6.5795     | 0     |
| 5.8251     | 1     |
| 5.3850     | 2     |
| 5.0469     | 3     |
| 4.8048     | 4     |
| 4.6144     | 5     |
| 4.4743     | 6     |
| 4.3366     | 7     |
| 4.2178     | 8     |
| 4.1022     | 9     |
| 3.9908     | 10    |
| 3.8856     | 11    |
| 3.7700     | 12    |
| 3.6673     | 13    |
| 3.5560     | 14    |
| 3.4401     | 15    |
| 3.3328     | 16    |
| 3.2248     | 17    |
| 3.1290     | 18    |
| 3.0121     | 19    |
| 2.8978     | 20    |
| 2.7830     | 21    |
| 2.6913     | 22    |
| 2.5822     | 23    |
| 2.4772     | 24    |
| 2.3761     | 25    |
| 2.2792     | 26    |
| 2.1664     | 27    |
| 2.0731     | 28    |
| 1.9734     | 29    |
| 1.8900     | 30    |
| 1.7927     | 31    |
| 1.7036     | 32    |
| 1.6202     | 33    |
| 1.5329     | 34    |
| 1.4535     | 35    |
| 1.3778     | 36    |
| 1.3093     | 37    |
| 1.2413     | 38    |
| 1.1709     | 39    |
| 1.1114     | 40    |
| 1.0563     | 41    |
| 0.9950     | 42    |
| 0.9344     | 43    |
| 0.8830     | 44    |
| 0.8380     | 45    |
| 0.7966     | 46    |
| 0.7552     | 47    |
| 0.7162     | 48    |
| 0.6754     | 49    |
| 0.6420     | 50    |
| 0.6081     | 51    |
| 0.5825     | 52    |
| 0.5506     | 53    |
| 0.5213     | 54    |
| 0.4942     | 55    |
| 0.4716     | 56    |
| 0.4485     | 57    |
| 0.4256     | 58    |
| 0.4087     | 59    |
| 0.3921     | 60    |
| 0.3736     | 61    |
| 0.3574     | 62    |
| 0.3412     | 63    |
| 0.3272     | 64    |


### Framework versions

- Transformers 4.44.0
- TensorFlow 2.16.1
- Datasets 2.21.0
- Tokenizers 0.19.1