readme: ---
  language:
  - ab
  license: apache-2.0
  tags:
  - ab
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - model_for_talk
  - mozilla-foundation/common_voice_8_0
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: XLS-R-300M - Abkhaz
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: ab
      metrics:
      - name: Test WER
        type: wer
        value: 27.6
      - name: Test CER
        type: cer
        value: 4.577
  ---
  
  <!-- 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-abkhaz-cv8
  
  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 - AB dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1614
  - Wer: 0.2907
  
  ## 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: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 4000
  - num_epochs: 50.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 1.2881        | 4.26  | 4000  | 0.3764          | 0.6461 |
  | 1.0767        | 8.53  | 8000  | 0.2657          | 0.5164 |
  | 0.9841        | 12.79 | 12000 | 0.2330          | 0.4445 |
  | 0.9274        | 17.06 | 16000 | 0.2134          | 0.3929 |
  | 0.8781        | 21.32 | 20000 | 0.1945          | 0.3886 |
  | 0.8381        | 25.59 | 24000 | 0.1840          | 0.3737 |
  | 0.8054        | 29.85 | 28000 | 0.1756          | 0.3523 |
  | 0.7763        | 34.12 | 32000 | 0.1745          | 0.3299 |
  | 0.7474        | 38.38 | 36000 | 0.1677          | 0.3074 |
  | 0.7298        | 42.64 | 40000 | 0.1649          | 0.2963 |
  | 0.7125        | 46.91 | 44000 | 0.1617          | 0.2931 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  