readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - amazon_reviews_multi
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: electra-small-finetuned-amazon-review
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: amazon_reviews_multi
        type: amazon_reviews_multi
        args: en
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.5504
      - name: F1
        type: f1
        value: 0.5457527808330634
      - name: Precision
        type: precision
        value: 0.5428695841337288
      - name: Recall
        type: recall
        value: 0.5504
  ---
  
  <!-- 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. -->
  
  # electra-small-finetuned-amazon-review
  
  This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the amazon_reviews_multi dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0560
  - Accuracy: 0.5504
  - F1: 0.5458
  - Precision: 0.5429
  - Recall: 0.5504
  
  ## 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: 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: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 1.2172        | 1.0   | 1000 | 1.1014          | 0.5216   | 0.4902 | 0.4954    | 0.5216 |
  | 1.0027        | 2.0   | 2000 | 1.0388          | 0.549    | 0.5471 | 0.5494    | 0.549  |
  | 0.9035        | 3.0   | 3000 | 1.0560          | 0.5504   | 0.5458 | 0.5429    | 0.5504 |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.17.0
  - Tokenizers 0.10.3
  