readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - go_emotions-es-mt
  metrics:
  - accuracy
  - f1
  model-index:
  - name: electricidad-base-finetuned-go_emotions-es
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: go_emotions-es-mt
        type: go_emotions-es-mt
        config: simplified
        split: train
        args: simplified
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.5934476693051891
      - name: F1
        type: f1
        value: 0.5806237685841615
        
  widget:
  - text: "Me gusta mucho su forma de ser"
  - text: "Es una persona muy extraña..."
  - text: "El dolor es desesperante"
  - text: "No me esperaba una evolución tan positiva"
  - text: "¡Dios mío, es enorme!"
  - text: "¡Agg! Está asqueroso."
  ---
  
  <!-- 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
  
  This model is a fine-tuned version of [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on the [go_emotions-es-mt](https://huggingface.co/datasets/mrm8488/go_emotions-es-mt) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.5111
  - Accuracy: 0.5934
  - F1: 0.5806
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | 1.729         | 1.0   | 2270  | 1.5835          | 0.5578   | 0.5044 |
  | 1.4432        | 2.0   | 4540  | 1.4529          | 0.5842   | 0.5538 |
  | 1.2688        | 3.0   | 6810  | 1.4445          | 0.5945   | 0.5770 |
  | 1.1017        | 4.0   | 9080  | 1.4804          | 0.5937   | 0.5781 |
  | 0.9999        | 5.0   | 11350 | 1.5111          | 0.5934   | 0.5806 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  