readme: ---
  license: apache-2.0
  language:
  - lv
  tags:
  - generated_from_trainer
  - hf-asr-leaderboard
  - robust-speech-event
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-1B-common_voice7-lv-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: 11.179
      - name: Test CER
        type: cer
        value: 2.78
    - 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: 44.33
    - 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: 50.89
  ---
  
  <!-- 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_voice7-lv-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: 0.1582
  - Wer: 0.1137
  
  ## 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: 24
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 48
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 900
  - num_epochs: 100
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.6292        | 5.26  | 500  | 1.5562          | 0.9263 |
  | 0.1303        | 10.53 | 1000 | 0.8107          | 0.7666 |
  | 0.0974        | 15.79 | 1500 | 0.5290          | 0.4979 |
  | 0.0724        | 21.05 | 2000 | 0.2941          | 0.2247 |
  | 0.0591        | 26.32 | 2500 | 0.2838          | 0.2125 |
  | 0.0494        | 31.58 | 3000 | 0.2589          | 0.2102 |
  | 0.0417        | 36.84 | 3500 | 0.1987          | 0.1760 |
  | 0.0375        | 42.11 | 4000 | 0.1934          | 0.1690 |
  | 0.031         | 47.37 | 4500 | 0.1630          | 0.1460 |
  | 0.027         | 52.63 | 5000 | 0.1957          | 0.1447 |
  | 0.0256        | 57.89 | 5500 | 0.1747          | 0.1368 |
  | 0.0206        | 63.16 | 6000 | 0.1602          | 0.1299 |
  | 0.0178        | 68.42 | 6500 | 0.1809          | 0.1273 |
  | 0.0154        | 73.68 | 7000 | 0.1686          | 0.1216 |
  | 0.0137        | 78.95 | 7500 | 0.1585          | 0.1241 |
  | 0.0128        | 84.21 | 8000 | 0.1783          | 0.1278 |
  | 0.011         | 89.47 | 8500 | 0.1653          | 0.1228 |
  | 0.0096        | 94.74 | 9000 | 0.1620          | 0.1161 |
  | 0.0091        | 100.0 | 9500 | 0.1582          | 0.1137 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.10.3
  