readme: ---
  language:
  - et
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - robust-speech-event
  - et
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: xls-r-et-cv_8_0
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: et
      metrics:
      - name: Test WER
        type: wer
        value: 0.34180826781638346
      - name: Test CER
        type: cer
        value: 0.07356192733576256
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8.0
        type: mozilla-foundation/common_voice_8_0
        args: et
      metrics:
      - name: Test WER
        type: wer
        value: 34.18
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: et
      metrics:
      - name: Test WER
        type: wer
        value: 45.53
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: et
      metrics:
      - name: Test WER
        type: wer
        value: 54.41
  ---
  
  <!-- 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 - ET dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4623
  - Wer: 0.3420
  
  ## 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: 0.0003
  - train_batch_size: 72
  - eval_batch_size: 72
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 144
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.3082        | 12.5  | 500  | 0.3871          | 0.4907 |
  | 0.1497        | 25.0  | 1000 | 0.4168          | 0.4278 |
  | 0.1243        | 37.5  | 1500 | 0.4446          | 0.4220 |
  | 0.0954        | 50.0  | 2000 | 0.4426          | 0.3946 |
  | 0.0741        | 62.5  | 2500 | 0.4502          | 0.3800 |
  | 0.0533        | 75.0  | 3000 | 0.4618          | 0.3653 |
  | 0.0447        | 87.5  | 3500 | 0.4518          | 0.3461 |
  | 0.0396        | 100.0 | 4000 | 0.4623          | 0.3420 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.18.4.dev0
  - Tokenizers 0.11.0
  