readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-large-xls-r-300m-lv-v05
    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-large-xls-r-300m-lv-v05
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3862
  - Wer: 0.2588
  
  ## 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: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.8836        | 2.81  | 400  | 0.8722          | 0.7244 |
  | 0.5365        | 5.63  | 800  | 0.4622          | 0.4812 |
  | 0.277         | 8.45  | 1200 | 0.4348          | 0.4056 |
  | 0.1947        | 11.27 | 1600 | 0.4223          | 0.3636 |
  | 0.1655        | 14.08 | 2000 | 0.4084          | 0.3465 |
  | 0.1441        | 16.9  | 2400 | 0.4329          | 0.3497 |
  | 0.121         | 19.72 | 2800 | 0.4371          | 0.3324 |
  | 0.1062        | 22.53 | 3200 | 0.4202          | 0.3198 |
  | 0.0937        | 25.35 | 3600 | 0.4063          | 0.3265 |
  | 0.0871        | 28.17 | 4000 | 0.4253          | 0.3255 |
  | 0.0755        | 30.98 | 4400 | 0.4368          | 0.3194 |
  | 0.0627        | 33.8  | 4800 | 0.4067          | 0.2908 |
  | 0.0595        | 36.62 | 5200 | 0.3929          | 0.2973 |
  | 0.0523        | 39.44 | 5600 | 0.3748          | 0.2817 |
  | 0.0434        | 42.25 | 6000 | 0.3769          | 0.2711 |
  | 0.0391        | 45.07 | 6400 | 0.3901          | 0.2653 |
  | 0.0319        | 47.88 | 6800 | 0.3862          | 0.2588 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  