readme: ---
  language:
  - sv-SE
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - mozilla-foundation/common_voice_7_0
  - robust-speech-event
  - sv
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: XLS-R-300M - Swedish - CV7 - v2
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: sv-SE
      metrics:
      - name: Test WER
        type: wer
        value: 15.99
      - name: Test CER
        type: cer
        value: 5.2
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: sv
      metrics:
      - name: Test WER
        type: wer
        value: 24.41
      - name: Test CER
        type: cer
        value: 11.88
  ---
  
  <!-- 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: 0.2604
  - Wer: 0.2334
  
  ## 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
  - distributed_type: multi-GPU
  - num_devices: 8
  - gradient_accumulation_steps: 1
  - total_train_batch_size: 32
  - total_eval_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: 50.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  See Tensorboard
  
  ### Evaluation Commands
  
  1. To evaluate on `mozilla-foundation/common_voice_7_0` with split `test`
  
  ```bash
  python eval.py --model_id patrickvonplaten/xls-r-300-sv-cv7 --dataset mozilla-foundation/common_voice_7_0 --config sv-SE --split test
  ```
  
  2. To evaluate on `speech-recognition-community-v2/dev_data`
  
  ```bash
  python eval.py --model_id patrickvonplaten/xls-r-300-sv-cv7 --dataset speech-recognition-community-v2/dev_data --config sv --split validation --chunk_length_s 5.0 --stride_length_s 1.0
  ```
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.9.0+cu111
  - Datasets 1.18.4.dev0
  - Tokenizers 0.10.3
  