readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: electricidad-small-finetuned-restaurant-sentiment-analysis-usElectionTweets1Jul11Nov-spanish
    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. -->
  
  # electricidad-small-finetuned-restaurant-sentiment-analysis-usElectionTweets1Jul11Nov-spanish
  
  This model is a fine-tuned version of [mrm8488/electricidad-small-finetuned-restaurant-sentiment-analysis](https://huggingface.co/mrm8488/electricidad-small-finetuned-restaurant-sentiment-analysis) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.3534
  - Accuracy: 0.7585
  - F1: 0.7585
  
  ## 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: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 60
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | 0.8145        | 1.0   | 1222  | 0.7033          | 0.7168   | 0.7168 |
  | 0.7016        | 2.0   | 2444  | 0.5936          | 0.7731   | 0.7731 |
  | 0.6183        | 3.0   | 3666  | 0.5190          | 0.8046   | 0.8046 |
  | 0.5516        | 4.0   | 4888  | 0.4678          | 0.8301   | 0.8301 |
  | 0.4885        | 5.0   | 6110  | 0.3670          | 0.8713   | 0.8713 |
  | 0.4353        | 6.0   | 7332  | 0.3119          | 0.8987   | 0.8987 |
  | 0.3957        | 7.0   | 8554  | 0.2908          | 0.9084   | 0.9084 |
  | 0.3386        | 8.0   | 9776  | 0.2108          | 0.9348   | 0.9348 |
  | 0.2976        | 9.0   | 10998 | 0.1912          | 0.9422   | 0.9422 |
  | 0.2828        | 10.0  | 12220 | 0.1496          | 0.9591   | 0.9591 |
  | 0.243         | 11.0  | 13442 | 0.1326          | 0.9639   | 0.9639 |
  | 0.2049        | 12.0  | 14664 | 0.1249          | 0.9693   | 0.9693 |
  | 0.2041        | 13.0  | 15886 | 0.1049          | 0.9752   | 0.9752 |
  | 0.1855        | 14.0  | 17108 | 0.0816          | 0.9798   | 0.9798 |
  | 0.1637        | 15.0  | 18330 | 0.0733          | 0.9836   | 0.9836 |
  | 0.1531        | 16.0  | 19552 | 0.0577          | 0.9880   | 0.9880 |
  | 0.1221        | 17.0  | 20774 | 0.0581          | 0.9895   | 0.9895 |
  | 0.1207        | 18.0  | 21996 | 0.0463          | 0.9903   | 0.9903 |
  | 0.1152        | 19.0  | 23218 | 0.0472          | 0.9908   | 0.9908 |
  | 0.1028        | 20.0  | 24440 | 0.0356          | 0.9936   | 0.9936 |
  | 0.1027        | 21.0  | 25662 | 0.0278          | 0.9957   | 0.9957 |
  | 0.0915        | 22.0  | 26884 | 0.0344          | 0.9946   | 0.9946 |
  | 0.0887        | 23.0  | 28106 | 0.0243          | 0.9954   | 0.9954 |
  | 0.0713        | 24.0  | 29328 | 0.0208          | 0.9969   | 0.9969 |
  | 0.0749        | 25.0  | 30550 | 0.0198          | 0.9964   | 0.9964 |
  | 0.0699        | 26.0  | 31772 | 0.0153          | 0.9969   | 0.9969 |
  | 0.0567        | 27.0  | 32994 | 0.0144          | 0.9972   | 0.9972 |
  | 0.0613        | 28.0  | 34216 | 0.0105          | 0.9982   | 0.9982 |
  | 0.0567        | 29.0  | 35438 | 0.0117          | 0.9982   | 0.9982 |
  | 0.0483        | 30.0  | 36660 | 0.0072          | 0.9985   | 0.9985 |
  | 0.0469        | 31.0  | 37882 | 0.0063          | 0.9987   | 0.9987 |
  | 0.0485        | 32.0  | 39104 | 0.0067          | 0.9985   | 0.9985 |
  | 0.0464        | 33.0  | 40326 | 0.0020          | 0.9995   | 0.9995 |
  | 0.0472        | 34.0  | 41548 | 0.0036          | 0.9995   | 0.9995 |
  | 0.0388        | 35.0  | 42770 | 0.0016          | 0.9995   | 0.9995 |
  | 0.0248        | 36.0  | 43992 | 0.0047          | 0.9990   | 0.9990 |
  | 0.0396        | 37.0  | 45214 | 0.0004          | 0.9997   | 0.9997 |
  | 0.0331        | 38.0  | 46436 | 0.0020          | 0.9995   | 0.9995 |
  | 0.0292        | 39.0  | 47658 | 0.0000          | 1.0      | 1.0    |
  | 0.0253        | 40.0  | 48880 | 0.0001          | 1.0      | 1.0    |
  | 0.0285        | 41.0  | 50102 | 0.0000          | 1.0      | 1.0    |
  | 0.0319        | 42.0  | 51324 | 0.0000          | 1.0      | 1.0    |
  | 0.0244        | 43.0  | 52546 | 0.0000          | 1.0      | 1.0    |
  | 0.0261        | 44.0  | 53768 | 0.0001          | 1.0      | 1.0    |
  | 0.0256        | 45.0  | 54990 | 0.0000          | 1.0      | 1.0    |
  | 0.0258        | 46.0  | 56212 | 0.0000          | 1.0      | 1.0    |
  | 0.0173        | 47.0  | 57434 | 0.0000          | 1.0      | 1.0    |
  | 0.0253        | 48.0  | 58656 | 0.0000          | 1.0      | 1.0    |
  | 0.0241        | 49.0  | 59878 | 0.0000          | 1.0      | 1.0    |
  | 0.019         | 50.0  | 61100 | 0.0000       