readme: ---
  license: apache-2.0
  language:
  - sl
  tags:
  - generated_from_trainer
  - hf-asr-leaderboard
  - robust-speech-event
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-1B-common_voice-sl-ft
    results:
    - task:
        name: 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: 23.26
      - name: Test CER
        type: cer
        value: 7.95
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7.0
        type: mozilla-foundation/common_voice_7_0
        args: sl
      metrics:
      - name: Test WER
        type: wer
        value: 13.59
    - 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: 62.71
    - 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: 62.34
  ---
  
  <!-- 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-1B-common_voice-sl-ft
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2112
  - Wer: 0.1404
  
  ## 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: 3e-05
  - train_batch_size: 32
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 400
  - num_epochs: 100
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.8291        | 12.2  | 500  | 0.5674          | 0.7611 |
  | 0.0416        | 24.39 | 1000 | 0.3093          | 0.2964 |
  | 0.0256        | 36.59 | 1500 | 0.2224          | 0.2072 |
  | 0.0179        | 48.78 | 2000 | 0.2274          | 0.1960 |
  | 0.0113        | 60.98 | 2500 | 0.2078          | 0.1582 |
  | 0.0086        | 73.17 | 3000 | 0.1898          | 0.1552 |
  | 0.0059        | 85.37 | 3500 | 0.2054          | 0.1446 |
  | 0.0044        | 97.56 | 4000 | 0.2112          | 0.1404 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.10.3
  