readme: ---
  language:
  - ha
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - robust-speech-event
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: ''
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8.0
        type: mozilla-foundation/common_voice_8_0
        args: ha
      metrics:
      - name: Test WER
        type: wer
        value: 51.31
  ---
  
  <!-- 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. -->
  
  # 
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - HA dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4998
  - Wer: 0.5153
  
  ## 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: 9.6e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2000
  - num_epochs: 80.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.0021        | 8.33  | 500  | 2.9059          | 1.0    |
  | 2.6604        | 16.66 | 1000 | 2.6402          | 0.9892 |
  | 1.2216        | 24.99 | 1500 | 0.6051          | 0.6851 |
  | 1.0754        | 33.33 | 2000 | 0.5408          | 0.6464 |
  | 0.9582        | 41.66 | 2500 | 0.5521          | 0.5935 |
  | 0.8653        | 49.99 | 3000 | 0.5156          | 0.5550 |
  | 0.7867        | 58.33 | 3500 | 0.5439          | 0.5606 |
  | 0.7265        | 66.66 | 4000 | 0.4863          | 0.5255 |
  | 0.6699        | 74.99 | 4500 | 0.5050          | 0.5169 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu113
  - Datasets 1.18.4.dev0
  - Tokenizers 0.11.0
  