readme: ---
  license: apache-2.0
  tags:
  - audio-classification
  - generated_from_trainer
  datasets:
  - common_language
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-base-lang-id
    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. -->
  
  # wav2vec2-base-lang-id
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the anton-l/common_language dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9836
  - Accuracy: 0.7945
  
  ## 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: 0.0003
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 2.9568        | 1.0   | 173  | 3.2866          | 0.1146   |
  | 1.9243        | 2.0   | 346  | 2.1241          | 0.3840   |
  | 1.2923        | 3.0   | 519  | 1.5498          | 0.5489   |
  | 0.8659        | 4.0   | 692  | 1.4953          | 0.6126   |
  | 0.5539        | 5.0   | 865  | 1.2431          | 0.6926   |
  | 0.4101        | 6.0   | 1038 | 1.1443          | 0.7232   |
  | 0.2945        | 7.0   | 1211 | 1.0870          | 0.7544   |
  | 0.1552        | 8.0   | 1384 | 1.1080          | 0.7661   |
  | 0.0968        | 9.0   | 1557 | 0.9836          | 0.7945   |
  | 0.0623        | 10.0  | 1730 | 1.0252          | 0.7993   |
  
  
  ### Framework versions
  
  - Transformers 4.11.0.dev0
  - Pytorch 1.9.1+cu111
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  