readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: chinese-bert-wwm-chinese_bert_wwm1
    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_wwm1
  
  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: 0.0009
  
  ## 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: 16
  - eval_batch_size: 16
  - 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   | 71   | 0.5750          |
  | No log        | 2.0   | 142  | 0.0617          |
  | No log        | 3.0   | 213  | 0.0109          |
  | No log        | 4.0   | 284  | 0.0042          |
  | No log        | 5.0   | 355  | 0.0024          |
  | No log        | 6.0   | 426  | 0.0017          |
  | No log        | 7.0   | 497  | 0.0012          |
  | 0.5341        | 8.0   | 568  | 0.0009          |
  | 0.5341        | 9.0   | 639  | 0.0009          |
  | 0.5341        | 10.0  | 710  | 0.0011          |
  | 0.5341        | 11.0  | 781  | 0.0013          |
  | 0.5341        | 12.0  | 852  | 0.0012          |
  | 0.5341        | 13.0  | 923  | 0.0010          |
  | 0.5341        | 14.0  | 994  | 0.0010          |
  | 0.0041        | 15.0  | 1065 | 0.0011          |
  | 0.0041        | 16.0  | 1136 | 0.0009          |
  | 0.0041        | 17.0  | 1207 | 0.0008          |
  | 0.0041        | 18.0  | 1278 | 0.0009          |
  | 0.0041        | 19.0  | 1349 | 0.0008          |
  | 0.0041        | 20.0  | 1420 | 0.0008          |
  | 0.0041        | 21.0  | 1491 | 0.0009          |
  | 0.0019        | 22.0  | 1562 | 0.0009          |
  | 0.0019        | 23.0  | 1633 | 0.0010          |
  | 0.0019        | 24.0  | 1704 | 0.0009          |
  | 0.0019        | 25.0  | 1775 | 0.0009          |
  | 0.0019        | 26.0  | 1846 | 0.0008          |
  | 0.0019        | 27.0  | 1917 | 0.0009          |
  | 0.0019        | 28.0  | 1988 | 0.0009          |
  | 0.0013        | 29.0  | 2059 | 0.0009          |
  | 0.0013        | 30.0  | 2130 | 0.0009          |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.1
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  