readme: ---
  language:
  - lv
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - lv
  - model_for_talk
  - mozilla-foundation/common_voice_7_0
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: XLS-R-300M - Latvian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: lv
      metrics:
      - name: Test WER
        type: wer
        value: 16.977
      - name: Test CER
        type: cer
        value: 4.23
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: lv
      metrics:
      - name: Test WER
        type: wer
        value: 45.247
      - name: Test CER
        type: cer
        value: 16.924
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: lv
      metrics:
      - name: Test WER
        type: wer
        value: 56.16
  ---
  
  <!-- 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-latvian
  
  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 - LV dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1892
  - Wer: 0.1698
  
  ## 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: 1
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2000
  - num_epochs: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 1.4235        | 12.82 | 2000  | 0.4475          | 0.4551 |
  | 0.9383        | 25.64 | 4000  | 0.2235          | 0.2328 |
  | 0.8359        | 38.46 | 6000  | 0.2004          | 0.2098 |
  | 0.7633        | 51.28 | 8000  | 0.1960          | 0.1882 |
  | 0.7001        | 64.1  | 10000 | 0.1902          | 0.1809 |
  | 0.652         | 76.92 | 12000 | 0.1979          | 0.1775 |
  | 0.6025        | 89.74 | 14000 | 0.1866          | 0.1696 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  