readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: chinese-macbert-base-finetuned
    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-macbert-base-finetuned
  
  This model is a fine-tuned version of [hfl/chinese-macbert-base](https://huggingface.co/hfl/chinese-macbert-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2790
  - Accuracy: 0.9613
  - F1: 0.9548
  
  ## 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: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 1.9986        | 1.0   | 3    | 1.5298          | 0.8177   | 0.7357 |
  | 1.43          | 2.0   | 6    | 1.2166          | 0.8177   | 0.7357 |
  | 1.2494        | 3.0   | 9    | 1.0037          | 0.8177   | 0.7357 |
  | 0.9698        | 4.0   | 12   | 0.8538          | 0.8177   | 0.7357 |
  | 0.8999        | 5.0   | 15   | 0.7562          | 0.8453   | 0.7811 |
  | 0.8945        | 6.0   | 18   | 0.6813          | 0.8619   | 0.7980 |
  | 0.7059        | 7.0   | 21   | 0.6101          | 0.8619   | 0.7980 |
  | 0.6066        | 8.0   | 24   | 0.5422          | 0.8619   | 0.7983 |
  | 0.5938        | 9.0   | 27   | 0.4891          | 0.8619   | 0.7996 |
  | 0.5995        | 10.0  | 30   | 0.4493          | 0.8674   | 0.8124 |
  | 0.493         | 11.0  | 33   | 0.4113          | 0.8840   | 0.8470 |
  | 0.5175        | 12.0  | 36   | 0.3798          | 0.9116   | 0.8893 |
  | 0.4615        | 13.0  | 39   | 0.3536          | 0.9392   | 0.9218 |
  | 0.4339        | 14.0  | 42   | 0.3311          | 0.9337   | 0.9094 |
  | 0.3926        | 15.0  | 45   | 0.3147          | 0.9448   | 0.9317 |
  | 0.3507        | 16.0  | 48   | 0.3012          | 0.9503   | 0.9384 |
  | 0.3634        | 17.0  | 51   | 0.2926          | 0.9558   | 0.9471 |
  | 0.2825        | 18.0  | 54   | 0.2857          | 0.9613   | 0.9548 |
  | 0.308         | 19.0  | 57   | 0.2808          | 0.9613   | 0.9548 |
  | 0.3323        | 20.0  | 60   | 0.2790          | 0.9613   | 0.9548 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.12.0+cu102
  - Datasets 1.18.4
  - Tokenizers 0.12.1
  