readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - amazon_reviews_multi
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: electra-base-gen-finetuned-amazon-review
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: amazon_reviews_multi
        type: amazon_reviews_multi
        args: es
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.5024
      - name: F1
        type: f1
        value: 0.5063190059782597
      - name: Precision
        type: precision
        value: 0.5121183330982292
      - name: Recall
        type: recall
        value: 0.5024
  ---
  
  <!-- 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-base-gen-finetuned-amazon-review
  
  This model is a fine-tuned version of [mrm8488/electricidad-base-generator](https://huggingface.co/mrm8488/electricidad-base-generator) on the amazon_reviews_multi dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8030
  - Accuracy: 0.5024
  - F1: 0.5063
  - Precision: 0.5121
  - Recall: 0.5024
  
  ## 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: 7
  
  ### Training results
  
  | Training Loss | Epoch | Step | Accuracy | F1     | Validation Loss | Precision | Recall |
  |:-------------:|:-----:|:----:|:--------:|:------:|:---------------:|:---------:|:------:|
  | 0.5135        | 1.0   | 1000 | 0.4886   | 0.4929 | 1.6580          | 0.5077    | 0.4886 |
  | 0.4138        | 2.0   | 2000 | 0.5044   | 0.5093 | 1.7951          | 0.5183    | 0.5044 |
  | 0.4244        | 3.0   | 3000 | 0.5022   | 0.5068 | 1.8108          | 0.5141    | 0.5022 |
  | 0.4231        | 6.0   | 6000 | 1.7636   | 0.4972 | 0.5018          | 0.5092    | 0.4972 |
  | 0.3574        | 7.0   | 7000 | 1.8030   | 0.5024 | 0.5063          | 0.5121    | 0.5024 |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.17.0
  - Tokenizers 0.10.3
  