readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-xls-r-300m-arabic_speech_commands_half
    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-xls-r-300m-arabic_speech_commands_half
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2678
  - Accuracy: 0.9975
  
  ## 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: 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 3.6816        | 0.99  | 28   | 3.4693          | 0.1575   |
  | 3.0227        | 1.99  | 56   | 2.5330          | 0.2775   |
  | 2.3345        | 2.99  | 84   | 1.8723          | 0.5925   |
  | 1.6785        | 3.99  | 112  | 1.2944          | 0.8092   |
  | 1.2606        | 4.99  | 140  | 0.8933          | 0.9425   |
  | 1.0024        | 5.99  | 168  | 0.6041          | 0.9817   |
  | 0.6478        | 6.99  | 196  | 0.3814          | 0.9933   |
  | 0.4768        | 7.99  | 224  | 0.2678          | 0.9975   |
  | 0.4143        | 8.99  | 252  | 0.2198          | 0.9967   |
  | 0.3278        | 9.99  | 280  | 0.1993          | 0.9967   |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  