readme: ---
  license: cc-by-nc-sa-4.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: test-finetuned-ner
    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. -->
  
  # test-finetuned-ner
  
  This model is a fine-tuned version of [hfl/chinese-pert-large](https://huggingface.co/hfl/chinese-pert-large) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1687
  - Precision: 0.7449
  - Recall: 0.7717
  - F1: 0.7581
  - Accuracy: 0.9546
  
  ## 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: 3
  - eval_batch_size: 3
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.1234        | 1.0   | 9387  | 0.1513          | 0.6954    | 0.7365 | 0.7153 | 0.9505   |
  | 0.0841        | 2.0   | 18774 | 0.1462          | 0.7248    | 0.7630 | 0.7434 | 0.9533   |
  | 0.0542        | 3.0   | 28161 | 0.1687          | 0.7449    | 0.7717 | 0.7581 | 0.9546   |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.8.0+cu111
  - Datasets 2.4.0
  - Tokenizers 0.10.3
  