readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - sem_eval2010_task8
  metrics:
  - accuracy
  model-index:
  - name: bert-base-chinese-finetuned-fdRE
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: sem_eval2010_task8
        type: sem_eval2010_task8
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9080962800875274
  ---
  
  <!-- 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. -->
  
  # bert-base-chinese-finetuned-fdRE
  
  This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on the sem_eval2010_task8 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2716
  - Accuracy: 0.9081
  
  ## 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: 10
  - eval_batch_size: 10
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 46   | 0.5571          | 0.7812   |
  | No log        | 2.0   | 92   | 0.4030          | 0.8621   |
  | No log        | 3.0   | 138  | 0.3139          | 0.8928   |
  | No log        | 4.0   | 184  | 0.2716          | 0.9081   |
  | No log        | 5.0   | 230  | 0.2564          | 0.9081   |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  