readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: hubert-base-ls960-finetuned-speech-commands
    results: []
  datasets:
  - mazkooleg/google_speech_commands_augmented_raw
  ---
  
  <!-- 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. -->
  
  # hubert-base-ls960-finetuned-speech-commands
  
  This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the None dataset.
  It achieves the following results on the evaluation set:
  - Accuracy: 0.9964
  - Loss: 0.0192
  
  ## 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: 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Accuracy | Validation Loss |
  |:-------------:|:-----:|:-----:|:--------:|:---------------:|
  | 0.1264        | 1.0   | 8558  | 0.9950   | 0.0242          |
  | 0.0637        | 2.0   | 17116 | 0.9964   | 0.0165          |
  | 0.0694        | 3.0   | 25674 | 0.9961   | 0.0200          |
  | 0.0593        | 4.0   | 34232 | 0.9961   | 0.0217          |
  | 0.0574        | 5.0   | 42790 | 0.9964   | 0.0192          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.11.0+cpu
  - Datasets 2.8.0
  - Tokenizers 0.12.1