readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: twitter-data-pysentimiento-robertuito-sentiment-finetuned-memes
    results: []
  ---
  
  <!-- 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. -->
  
  # twitter-data-pysentimiento-robertuito-sentiment-finetuned-memes
  
  This model is a fine-tuned version of [pysentimiento/robertuito-sentiment-analysis](https://huggingface.co/pysentimiento/robertuito-sentiment-analysis) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2563
  - Accuracy: 0.9262
  - Precision: 0.9271
  - Recall: 0.9262
  - F1: 0.9263
  
  ## 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: 1e-05
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 6
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.3641        | 1.0   | 1762  | 0.3197          | 0.8999   | 0.9001    | 0.8999 | 0.8995 |
  | 0.272         | 2.0   | 3524  | 0.2723          | 0.9171   | 0.9181    | 0.9171 | 0.9171 |
  | 0.2451        | 3.0   | 5286  | 0.2633          | 0.9224   | 0.9226    | 0.9224 | 0.9223 |
  | 0.2084        | 4.0   | 7048  | 0.2518          | 0.9256   | 0.9270    | 0.9256 | 0.9257 |
  | 0.199         | 5.0   | 8810  | 0.2545          | 0.9268   | 0.9277    | 0.9268 | 0.9269 |
  | 0.1926        | 6.0   | 10572 | 0.2563          | 0.9262   | 0.9271    | 0.9262 | 0.9263 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  