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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: hfl/chinese-bert-wwm
model-index:
- name: chinese-bert-wwm-chinese_bert_wwm3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# chinese-bert-wwm-chinese_bert_wwm3
This model is a fine-tuned version of [hfl/chinese-bert-wwm](https://huggingface.co/hfl/chinese-bert-wwm) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
## 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:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 72 | 0.4251 |
| No log | 2.0 | 144 | 0.0282 |
| No log | 3.0 | 216 | 0.0048 |
| No log | 4.0 | 288 | 0.0018 |
| No log | 5.0 | 360 | 0.0011 |
| No log | 6.0 | 432 | 0.0006 |
| 0.483 | 7.0 | 504 | 0.0004 |
| 0.483 | 8.0 | 576 | 0.0004 |
| 0.483 | 9.0 | 648 | 0.0002 |
| 0.483 | 10.0 | 720 | 0.0002 |
| 0.483 | 11.0 | 792 | 0.0002 |
| 0.483 | 12.0 | 864 | 0.0001 |
| 0.483 | 13.0 | 936 | 0.0001 |
| 0.0031 | 14.0 | 1008 | 0.0001 |
| 0.0031 | 15.0 | 1080 | 0.0001 |
| 0.0031 | 16.0 | 1152 | 0.0001 |
| 0.0031 | 17.0 | 1224 | 0.0001 |
| 0.0031 | 18.0 | 1296 | 0.0001 |
| 0.0031 | 19.0 | 1368 | 0.0001 |
| 0.0031 | 20.0 | 1440 | 0.0001 |
| 0.0015 | 21.0 | 1512 | 0.0001 |
| 0.0015 | 22.0 | 1584 | 0.0001 |
| 0.0015 | 23.0 | 1656 | 0.0001 |
| 0.0015 | 24.0 | 1728 | 0.0001 |
| 0.0015 | 25.0 | 1800 | 0.0000 |
| 0.0015 | 26.0 | 1872 | 0.0001 |
| 0.0015 | 27.0 | 1944 | 0.0000 |
| 0.001 | 28.0 | 2016 | 0.0000 |
| 0.001 | 29.0 | 2088 | 0.0000 |
| 0.001 | 30.0 | 2160 | 0.0000 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.9.1
- Datasets 1.13.3
- Tokenizers 0.10.3
|