readme: ---
  language:
  - ha
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - ha
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: XLS-R-300M - Hausa
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: ha
      metrics:
      - name: Test WER
        type: wer
        value: 100
      - name: Test CER
        type: cer
        value: 132.32
  ---
  
  <!-- 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-large-xls-r-300m-hausa
  
  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_7_0 - HA dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5756
  - Wer: 0.6014
  
  ## 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: 7e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.7064        | 11.36 | 500  | 2.7112          | 1.0    |
  | 1.3079        | 22.73 | 1000 | 0.7337          | 0.7776 |
  | 1.0919        | 34.09 | 1500 | 0.5938          | 0.7023 |
  | 0.9546        | 45.45 | 2000 | 0.5698          | 0.6133 |
  | 0.8895        | 56.82 | 2500 | 0.5739          | 0.6142 |
  | 0.8152        | 68.18 | 3000 | 0.5579          | 0.6091 |
  | 0.7703        | 79.55 | 3500 | 0.5813          | 0.6210 |
  | 0.732         | 90.91 | 4000 | 0.5756          | 0.5860 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  