readme: ---
  language:
  - or
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_9_0
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_9_0
  metrics:
  - wer
  model-index:
  - name: XLS-R-300M - Odia
    results:
    - task:
        type: automatic-speech-recognition
        name: Speech Recognition
      dataset:
        type: mozilla-foundation/common_voice_9_0
        name: Common Voice 9
        args: or
      metrics:
      - type: wer
        value: 44.343
        name: Test WER
      - name: Test CER
        type: cer
        value: 10.989
  ---
  
  <!-- 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_9_0 - OR dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7886
  - Wer: 0.5495
  - Cer: 0.1311
  
  ## 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: 7.5e-05
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - training_steps: 3071
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
  | 3.5875        | 66.62  | 400  | 3.4289          | 1.0    | 1.0    |
  | 1.4065        | 133.31 | 800  | 0.7243          | 0.6619 | 0.1734 |
  | 1.007         | 199.92 | 1200 | 0.6611          | 0.5831 | 0.1457 |
  | 0.7984        | 266.62 | 1600 | 0.6387          | 0.5520 | 0.1332 |
  | 0.6117        | 333.31 | 2000 | 0.7424          | 0.5682 | 0.1376 |
  | 0.4926        | 399.92 | 2400 | 0.7627          | 0.5514 | 0.1314 |
  | 0.416         | 466.62 | 2800 | 0.7816          | 0.5604 | 0.1320 |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.1.1.dev0
  - Tokenizers 0.12.1
  