readme: 
  ---
  language:
  - ka
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - robust-speech-event
  - hf-asr-leaderboard
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-xls-r-1b-ka
    results:
    - task:
        type: automatic-speech-recognition
        name: Speech Recognition
      dataset:
        type: mozilla-foundation/common_voice_8_0
        name: Common Voice ka
        args: ka
      metrics:
      - type: wer
        value: 7.39778066580026
        name: WER LM
      - type: cer
        value: 1.1882089427096434
        name: CER LM
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: ka
      metrics:
      - name: Test WER
        type: wer
        value: 22.61
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: ka
      metrics:
      - name: Test WER
        type: wer
        value: 21.58
  ---
  
  <!-- 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-1b-ka
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the /WORKSPACE/DATA/KA/NOIZY_STUDENT_2/ - KA dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1022
  - Wer: 0.1527
  - Cer: 0.0221
  
  ## 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: 16
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.1
  - training_steps: 4000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 1.2839        | 6.45  | 400  | 0.2229          | 0.3609 | 0.0557 |
  | 0.9775        | 12.9  | 800  | 0.1271          | 0.2202 | 0.0317 |
  | 0.9045        | 19.35 | 1200 | 0.1268          | 0.2030 | 0.0294 |
  | 0.8652        | 25.8  | 1600 | 0.1211          | 0.1940 | 0.0287 |
  | 0.8505        | 32.26 | 2000 | 0.1192          | 0.1912 | 0.0276 |
  | 0.8168        | 38.7  | 2400 | 0.1086          | 0.1763 | 0.0260 |
  | 0.7737        | 45.16 | 2800 | 0.1098          | 0.1753 | 0.0256 |
  | 0.744         | 51.61 | 3200 | 0.1054          | 0.1646 | 0.0239 |
  | 0.7114        | 58.06 | 3600 | 0.1034          | 0.1573 | 0.0228 |
  | 0.6773        | 64.51 | 4000 | 0.1022          | 0.1527 | 0.0221 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2
  - Datasets 1.18.4.dev0
  - Tokenizers 0.11.0
  