readme: ---
  language:
  - sl
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - sl
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: XLS-R-300M - Slovenian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: sl
      metrics:
      - name: Test WER
        type: wer
        value: 18.97
      - name: Test CER
        type: cer
        value: 4.534
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: sl
      metrics:
      - name: Test WER
        type: wer
        value: 55.048
      - name: Test CER
        type: cer
        value: 22.739
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: sl
      metrics:
      - name: Test WER
        type: wer
        value: 54.81
  ---
  
  <!-- 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-slovenian
  
  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 - SL dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2093
  - Wer: 0.1907
  
  ## 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: 1000
  - num_epochs: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.785         | 12.5  | 1000 | 0.7465          | 0.6812 |
  | 0.8989        | 25.0  | 2000 | 0.2495          | 0.2732 |
  | 0.7118        | 37.5  | 3000 | 0.2126          | 0.2284 |
  | 0.6367        | 50.0  | 4000 | 0.2049          | 0.2049 |
  | 0.5763        | 62.5  | 5000 | 0.2116          | 0.2055 |
  | 0.5196        | 75.0  | 6000 | 0.2111          | 0.1910 |
  | 0.4949        | 87.5  | 7000 | 0.2131          | 0.1931 |
  | 0.4797        | 100.0 | 8000 | 0.2093          | 0.1907 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  