readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-xls-r-300m-arabic_speech_commands_10s_one_speaker_5_classes_unknown
    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_10s_one_speaker_5_classes_unknown
  
  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: 0.7951
  - Accuracy: 0.8278
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 80
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 0.8   | 3    | 1.7933          | 0.2306   |
  | No log        | 1.8   | 6    | 1.7927          | 0.1667   |
  | No log        | 2.8   | 9    | 1.7908          | 0.1667   |
  | 2.1874        | 3.8   | 12   | 1.7836          | 0.225    |
  | 2.1874        | 4.8   | 15   | 1.7728          | 0.3083   |
  | 2.1874        | 5.8   | 18   | 1.6857          | 0.3889   |
  | 2.0742        | 6.8   | 21   | 1.4554          | 0.7333   |
  | 2.0742        | 7.8   | 24   | 1.2621          | 0.6861   |
  | 2.0742        | 8.8   | 27   | 1.0360          | 0.7528   |
  | 1.5429        | 9.8   | 30   | 1.0220          | 0.6472   |
  | 1.5429        | 10.8  | 33   | 0.7951          | 0.8278   |
  | 1.5429        | 11.8  | 36   | 0.7954          | 0.8111   |
  | 1.5429        | 12.8  | 39   | 0.6698          | 0.8167   |
  | 0.927         | 13.8  | 42   | 0.8400          | 0.6694   |
  | 0.927         | 14.8  | 45   | 0.7026          | 0.7194   |
  | 0.927         | 15.8  | 48   | 0.7232          | 0.6944   |
  | 0.429         | 16.8  | 51   | 0.6640          | 0.7333   |
  | 0.429         | 17.8  | 54   | 1.1750          | 0.6      |
  | 0.429         | 18.8  | 57   | 0.9270          | 0.6722   |
  | 0.2583        | 19.8  | 60   | 1.4541          | 0.5417   |
  | 0.2583        | 20.8  | 63   | 1.8917          | 0.4472   |
  | 0.2583        | 21.8  | 66   | 1.3213          | 0.6472   |
  | 0.2583        | 22.8  | 69   | 1.3114          | 0.7      |
  | 0.1754        | 23.8  | 72   | 0.8079          | 0.7389   |
  | 0.1754        | 24.8  | 75   | 1.6070          | 0.4861   |
  | 0.1754        | 25.8  | 78   | 1.6949          | 0.5083   |
  | 0.1348        | 26.8  | 81   | 1.4364          | 0.6472   |
  | 0.1348        | 27.8  | 84   | 0.9045          | 0.7889   |
  | 0.1348        | 28.8  | 87   | 1.1878          | 0.7111   |
  | 0.0634        | 29.8  | 90   | 0.9678          | 0.7667   |
  | 0.0634        | 30.8  | 93   | 0.9572          | 0.7889   |
  | 0.0634        | 31.8  | 96   | 0.8931          | 0.8139   |
  | 0.0634        | 32.8  | 99   | 1.4805          | 0.6583   |
  | 0.1267        | 33.8  | 102  | 2.6092          | 0.4778   |
  | 0.1267        | 34.8  | 105  | 2.2933          | 0.5306   |
  | 0.1267        | 35.8  | 108  | 1.9648          | 0.6083   |
  | 0.0261        | 36.8  | 111  | 1.8385          | 0.65     |
  | 0.0261        | 37.8  | 114  | 2.0328          | 0.6028   |
  | 0.0261        | 38.8  | 117  | 2.3722          | 0.55     |
  | 0.041         | 39.8  | 120  | 2.7606          | 0.4917   |
  | 0.041         | 40.8  | 123  | 2.5793          | 0.5056   |
  | 0.041         | 41.8  | 126  | 2.0967          | 0.5917   |
  | 0.041         | 42.8  | 129  | 1.7498          | 0.6611   |
  | 0.1004        | 43.8  | 132  | 1.6564          | 0.6722   |
  | 0.1004        | 44.8  | 135  | 1.7533          | 0.6583   |
  | 0.1004        | 45.8  | 138  | 2.3335          | 0.5806   |
  | 0.0688        | 46.8  | 141  | 2.9578          | 0.4778   |
  | 0.0688        | 47.8  | 144  | 3.2396          | 0.4472   |
  | 0.0688        | 48.8  | 147  | 3.2100          | 0.4528   |
  | 0.0082        | 49.8  | 150  | 3.2018          | 0.4472   |
  | 0.0082        | 50.8  | 153  | 3.1985          | 0.45     |
  | 0.0082        | 51.8  | 156  | 2.6950          | 0.525    |
  | 0.0082        | 52.8  | 159  | 2.2335          | 0.6056   |
  | 0.0159        | 53.8  | 162  | 2.0467          | 0.6306   |
  | 0.0159        | 54.8  | 165  | 1.8858          | 0.6583   |
  | 0.0159        | 55.8  | 168  | 1.8239          | 0.6694   |
  | 0.0083        | 56.8  | 171  | 1.7927          | 0.675    |
  | 0.0083        | 57.8  | 174  | 1.7636          | 0.6861   |
  | 0.0083     