readme: ---
  language:
  - bas
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - mozilla-foundation/common_voice_7_0
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: XLS-R-300M - Basaa
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: bas
      metrics:
      - name: Test WER
        type: wer
        value: 104.08
      - name: Test CER
        type: cer
        value: 228.48
  ---
  
  <!-- 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-basaa
  
  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 - BAS dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5975
  - Wer: 0.4981
  
  ## 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: 200.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 2.9287        | 15.62  | 500  | 2.8774          | 1.0    |
  | 1.1182        | 31.25  | 1000 | 0.6248          | 0.7131 |
  | 0.8329        | 46.88  | 1500 | 0.5573          | 0.5792 |
  | 0.7109        | 62.5   | 2000 | 0.5420          | 0.5683 |
  | 0.6295        | 78.12  | 2500 | 0.5166          | 0.5395 |
  | 0.5715        | 93.75  | 3000 | 0.5487          | 0.5629 |
  | 0.5016        | 109.38 | 3500 | 0.5370          | 0.5471 |
  | 0.4661        | 125.0  | 4000 | 0.5621          | 0.5395 |
  | 0.423         | 140.62 | 4500 | 0.5658          | 0.5248 |
  | 0.3793        | 156.25 | 5000 | 0.5921          | 0.4981 |
  | 0.3651        | 171.88 | 5500 | 0.5987          | 0.4888 |
  | 0.3351        | 187.5  | 6000 | 0.6017          | 0.4948 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  