readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - sibyl
  datasets:
  - amazon_polarity
  metrics:
  - accuracy
  model-index:
  - name: bert-base-uncased-amazon_polarity
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: amazon_polarity
        type: amazon_polarity
        args: amazon_polarity
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.94647
    - task:
        type: text-classification
        name: Text Classification
      dataset:
        name: amazon_polarity
        type: amazon_polarity
        config: amazon_polarity
        split: test
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9464875
        verified: true
      - name: Precision
        type: precision
        value: 0.9528844934702675
        verified: true
      - name: Recall
        type: recall
        value: 0.939425
        verified: true
      - name: AUC
        type: auc
        value: 0.9863499156250001
        verified: true
      - name: F1
        type: f1
        value: 0.9461068798388619
        verified: true
      - name: loss
        type: loss
        value: 0.2944573760032654
        verified: true
  ---
  
  <!-- 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-uncased-amazon_polarity
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the amazon_polarity dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2945
  - Accuracy: 0.9465
  
  ## 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: 5e-05
  - train_batch_size: 1
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1782000
  - training_steps: 17820000
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Accuracy |
  |:-------------:|:-----:|:------:|:---------------:|:--------:|
  | 0.7155        | 0.0   | 2000   | 0.7060          | 0.4622   |
  | 0.7054        | 0.0   | 4000   | 0.6925          | 0.5165   |
  | 0.6842        | 0.0   | 6000   | 0.6653          | 0.6116   |
  | 0.6375        | 0.0   | 8000   | 0.5721          | 0.7909   |
  | 0.4671        | 0.0   | 10000  | 0.3238          | 0.8770   |
  | 0.3403        | 0.0   | 12000  | 0.3692          | 0.8861   |
  | 0.4162        | 0.0   | 14000  | 0.4560          | 0.8908   |
  | 0.4728        | 0.0   | 16000  | 0.5071          | 0.8980   |
  | 0.5111        | 0.01  | 18000  | 0.5204          | 0.9015   |
  | 0.4792        | 0.01  | 20000  | 0.5193          | 0.9076   |
  | 0.544         | 0.01  | 22000  | 0.4835          | 0.9133   |
  | 0.4745        | 0.01  | 24000  | 0.4689          | 0.9170   |
  | 0.4403        | 0.01  | 26000  | 0.4778          | 0.9177   |
  | 0.4405        | 0.01  | 28000  | 0.4754          | 0.9163   |
  | 0.4375        | 0.01  | 30000  | 0.4808          | 0.9175   |
  | 0.4628        | 0.01  | 32000  | 0.4340          | 0.9244   |
  | 0.4488        | 0.01  | 34000  | 0.4162          | 0.9265   |
  | 0.4608        | 0.01  | 36000  | 0.4031          | 0.9271   |
  | 0.4478        | 0.01  | 38000  | 0.4502          | 0.9253   |
  | 0.4237        | 0.01  | 40000  | 0.4087          | 0.9279   |
  | 0.4601        | 0.01  | 42000  | 0.4133          | 0.9269   |
  | 0.4153        | 0.01  | 44000  | 0.4230          | 0.9306   |
  | 0.4096        | 0.01  | 46000  | 0.4108          | 0.9301   |
  | 0.4348        | 0.01  | 48000  | 0.4138          | 0.9309   |
  | 0.3787        | 0.01  | 50000  | 0.4066          | 0.9324   |
  | 0.4172        | 0.01  | 52000  | 0.4812          | 0.9206   |
  | 0.3897        | 0.02  | 54000  | 0.4013          | 0.9325   |
  | 0.3787        | 0.02  | 56000  | 0.3837          | 0.9344   |
  | 0.4253        | 0.02  | 58000  | 0.3925          | 0.9347   |
  | 0.3959        | 0.02  | 60000  | 0.3907          | 0.9353   |
  | 0.4402        | 0.02  | 62000  | 0.3708          | 0.9341   |
  | 0.4115        | 0.02  | 64000  | 0.3477          | 0.9361   |
  | 0.3876        | 0.02  | 66000  | 0.3634          | 0.9373   |
  | 0.4286        | 0.02  | 68000  | 0.3778          | 0.9378   |
  | 0.422         | 0.02  | 70000  | 0.3540          | 0.9361   |
  | 0.3732        | 0.02  | 72000  | 0.3853          | 0.9378   |
  | 0.3641        | 0.02  | 74000  | 0.3951          | 0.9386   |
  | 0.3701        | 0.02  | 76000  | 0.3582          | 0.9388   |
  | 0.4498        | 0.02  | 78000  | 0.3268          | 0.9375   |
  | 0.3587        | 0.02  | 80000  | 0.3825          | 0.9401   |
  | 0.4474        | 0.02  | 82000  | 0.3155          | 0.9391   |
  | 0.3598        | 0.02  | 84000  | 0.3666          | 0.9388   |
  | 0.389         | 0.02  | 86000  | 0.3745          | 0.9377 