readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: finetuning-pysentimiento-war-tweets
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  # finetuning-pysentimiento-war-tweets
  
  This model is a fine-tuned version of [finiteautomata/beto-sentiment-analysis](https://huggingface.co/finiteautomata/beto-sentiment-analysis) on a dataset of 1500 tweets from Peruvian accounts. It achieves the following results on the evaluation set:
  - Loss: 1.7689
  - Accuracy: 0.7378
  - F1: 0.7456
  
  ## Model description
  
  This model in a fine-tuned version of [finiteautomata/beto-sentiment-analysis](https://huggingface.co/finiteautomata/beto-sentiment-analysis) using five labels: **pro_russia**, **against_ukraine**, **neutral**, **against_russia**, **pro_ukraine**.
  
  ## Intended uses & limitations
  
  This model shall be used to classify text (more specifically, Spanish tweets) as expressing a position concerning the Russo-Ukrainian war.
  
  ## Training and evaluation data
  
  We used an 80/20 training/test split on the aforementioned dataset.
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 2e-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: 30
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  