readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - go_emotions
  metrics:
  - accuracy
  - f1
  model-index:
  - name: electricidad-base-finetuned-go_emotions-es-2
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: go_emotions
        type: go_emotions
        config: simplified
        split: train
        args: simplified
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.5591468777484608
      - name: F1
        type: f1
        value: 0.5581665299693344
  ---
  
  <!-- 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. -->
  
  # electricidad-base-finetuned-go_emotions-es-2
  
  This model is a fine-tuned version of [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on the go_emotions dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.0837
  - Accuracy: 0.5591
  - F1: 0.5582
  
  ## 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: 16
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | 1.7525        | 1.0   | 2270  | 1.6088          | 0.5618   | 0.5076 |
  | 1.4522        | 2.0   | 4540  | 1.4687          | 0.5807   | 0.5534 |
  | 1.2798        | 3.0   | 6810  | 1.4550          | 0.5910   | 0.5773 |
  | 1.0825        | 4.0   | 9080  | 1.5068          | 0.5873   | 0.5726 |
  | 0.9214        | 5.0   | 11350 | 1.6168          | 0.5776   | 0.5743 |
  | 0.7696        | 6.0   | 13620 | 1.7338          | 0.5776   | 0.5722 |
  | 0.6688        | 7.0   | 15890 | 1.8733          | 0.5631   | 0.5596 |
  | 0.553         | 8.0   | 18160 | 1.9571          | 0.5574   | 0.5591 |
  | 0.4626        | 9.0   | 20430 | 2.0499          | 0.5646   | 0.5625 |
  | 0.4399        | 10.0  | 22700 | 2.0837          | 0.5591   | 0.5582 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  