readme: ---
  language:
  - ro
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - mozilla-foundation/common_voice_8_0
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: wav2vec2-xls-r-300m-CV8-ro
    results: []
  ---
  
  <!-- 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-xls-r-300m-CV8-ro
  
  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_8_0 - RO dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1578
  - Wer: 0.6040
  - Cer: 0.0475
  
  ## 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: 0.0003
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - 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: 2000
  - num_epochs: 50.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 2.9736        | 3.62  | 500  | 2.9508          | 1.0    | 1.0    |
  | 1.3293        | 7.25  | 1000 | 0.3330          | 0.8407 | 0.0862 |
  | 0.956         | 10.87 | 1500 | 0.2042          | 0.6872 | 0.0602 |
  | 0.9509        | 14.49 | 2000 | 0.2184          | 0.7088 | 0.0652 |
  | 0.9272        | 18.12 | 2500 | 0.2312          | 0.7211 | 0.0703 |
  | 0.8561        | 21.74 | 3000 | 0.2158          | 0.6838 | 0.0631 |
  | 0.8258        | 25.36 | 3500 | 0.1970          | 0.6844 | 0.0601 |
  | 0.7993        | 28.98 | 4000 | 0.1895          | 0.6698 | 0.0577 |
  | 0.7525        | 32.61 | 4500 | 0.1845          | 0.6453 | 0.0550 |
  | 0.7211        | 36.23 | 5000 | 0.1781          | 0.6274 | 0.0531 |
  | 0.677         | 39.85 | 5500 | 0.1732          | 0.6188 | 0.0514 |
  | 0.6517        | 43.48 | 6000 | 0.1691          | 0.6177 | 0.0503 |
  | 0.6326        | 47.1  | 6500 | 0.1619          | 0.6045 | 0.0479 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  