readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - dataset
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilbert-base-multilingual-cased-finetuned-with-spanish-tweets-clf
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: dataset
        type: dataset
        config: 60-20-20
        split: dev
        args: 60-20-20
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.6005528680027643
      - name: F1
        type: f1
        value: 0.5980973383983778
      - name: Precision
        type: precision
        value: 0.6008849518067042
      - name: Recall
        type: recall
        value: 0.5962561389203832
  ---
  
  <!-- 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. -->
  
  # distilbert-base-multilingual-cased-finetuned-with-spanish-tweets-clf
  
  This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4692
  - Accuracy: 0.6006
  - F1: 0.5981
  - Precision: 0.6009
  - Recall: 0.5963
  
  ## 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: 8
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 1.0168        | 1.0   | 543  | 0.9144          | 0.5563   | 0.5012 | 0.5240    | 0.5251 |
  | 0.8197        | 2.0   | 1086 | 0.9133          | 0.5764   | 0.5476 | 0.5815    | 0.5462 |
  | 0.5574        | 3.0   | 1629 | 1.0629          | 0.6151   | 0.6150 | 0.6227    | 0.6112 |
  | 0.3487        | 4.0   | 2172 | 1.4692          | 0.6006   | 0.5981 | 0.6009    | 0.5963 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  