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---
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: 0.4942
- Epoch: 55
## 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 |
### Framework versions
- Transformers 4.44.0
- TensorFlow 2.16.1
- Datasets 2.21.0
- Tokenizers 0.19.1
|