readme: ---
  license: apache-2.0
  tags:
  - audio-classification
  - generated_from_trainer
  datasets:
  - common_language
  metrics:
  - accuracy
  model-index:
  - name: distilhubert-ft-common-language
    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. -->
  
  # distilhubert-ft-common-language
  
  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the common_language dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.7214
  - Accuracy: 0.2797
  
  ## 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: 3e-05
  - train_batch_size: 32
  - eval_batch_size: 4
  - seed: 0
  - 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: 10.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 3.6543        | 1.0   | 173  | 3.7611          | 0.0491   |
  | 3.2221        | 2.0   | 346  | 3.4868          | 0.1352   |
  | 2.9332        | 3.0   | 519  | 3.2732          | 0.1861   |
  | 2.7299        | 4.0   | 692  | 3.0944          | 0.2172   |
  | 2.5638        | 5.0   | 865  | 2.9790          | 0.2400   |
  | 2.3871        | 6.0   | 1038 | 2.8668          | 0.2590   |
  | 2.3384        | 7.0   | 1211 | 2.7972          | 0.2653   |
  | 2.2648        | 8.0   | 1384 | 2.7625          | 0.2695   |
  | 2.2162        | 9.0   | 1557 | 2.7405          | 0.2782   |
  | 2.1915        | 10.0  | 1730 | 2.7214          | 0.2797   |
  
  
  ### Framework versions
  
  - Transformers 4.12.0.dev0
  - Pytorch 1.9.1+cu111
  - Datasets 1.14.0
  - Tokenizers 0.10.3
  