readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-base-finetuned-sentiment-mesd
    results: []
  ---
  
  # wav2vec2-base-finetuned-sentiment-mesd
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the [MESD](https://huggingface.co/hackathon-pln-es/MESD) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5729
  - Accuracy: 0.8308
  
  ## Model description
  
  This model was trained to classify underlying sentiment of Spanish audio/speech.
  
  ## 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: 1.25e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 7    | 0.5729          | 0.8308   |
  | No log        | 2.0   | 14   | 0.6577          | 0.8      |
  | 0.1602        | 3.0   | 21   | 0.7055          | 0.8      |
  | 0.1602        | 4.0   | 28   | 0.8696          | 0.7615   |
  | 0.1602        | 5.0   | 35   | 0.6807          | 0.7923   |
  | 0.1711        | 6.0   | 42   | 0.7303          | 0.7923   |
  | 0.1711        | 7.0   | 49   | 0.7028          | 0.8077   |
  | 0.1711        | 8.0   | 56   | 0.7368          | 0.8      |
  | 0.1608        | 9.0   | 63   | 0.7190          | 0.7923   |
  | 0.1608        | 10.0  | 70   | 0.6913          | 0.8077   |
  | 0.1608        | 11.0  | 77   | 0.7047          | 0.8077   |
  | 0.1753        | 12.0  | 84   | 0.6801          | 0.8      |
  | 0.1753        | 13.0  | 91   | 0.7208          | 0.7769   |
  | 0.1753        | 14.0  | 98   | 0.7458          | 0.7846   |
  | 0.203         | 15.0  | 105  | 0.6494          | 0.8077   |
  | 0.203         | 16.0  | 112  | 0.6256          | 0.8231   |
  | 0.203         | 17.0  | 119  | 0.6788          | 0.8      |
  | 0.1919        | 18.0  | 126  | 0.6757          | 0.7846   |
  | 0.1919        | 19.0  | 133  | 0.6859          | 0.7846   |
  | 0.1641        | 20.0  | 140  | 0.6832          | 0.7846   |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.10.3
  