readme: ---
  language:
  - sv-SE
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: ''
    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. -->
  
  # 
  
  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_7_0 - SV-SE dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8004
  - Wer: 0.7139
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 8
  - 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: 2000
  - num_epochs: 10.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.6683        | 1.45  | 500  | 1.7698          | 1.0041 |
  | 1.9548        | 2.91  | 1000 | 1.0890          | 0.8602 |
  | 1.9568        | 4.36  | 1500 | 1.0878          | 0.8680 |
  | 1.9497        | 5.81  | 2000 | 1.1501          | 0.8838 |
  | 1.8453        | 7.27  | 2500 | 1.0452          | 0.8418 |
  | 1.6952        | 8.72  | 3000 | 0.9153          | 0.7823 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.1.dev0
  - Tokenizers 0.10.3
  