readme: ---
  language:
  - fi
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - fi
  - generated_from_trainer
  - hf-asr-leaderboard
  - model_for_talk
  - mozilla-foundation/common_voice_7_0
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: XLS-R-300M - Finnish
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: fi
      metrics:
      - name: Test WER
        type: wer
        value: 29.97
      - name: Test CER
        type: cer
        value: NA
  ---
  
  <!-- 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-finnish
  
  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 - FI dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2307
  - Wer: 0.2984
  
  ## 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: 7e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 70.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.9032        | 4.39  | 500  | 2.8768          | 1.0    |
  | 1.5724        | 8.77  | 1000 | 0.5638          | 0.6438 |
  | 1.1818        | 13.16 | 1500 | 0.3338          | 0.4759 |
  | 1.0798        | 17.54 | 2000 | 0.2876          | 0.4086 |
  | 1.0296        | 21.93 | 2500 | 0.2694          | 0.4248 |
  | 1.0014        | 26.32 | 3000 | 0.2626          | 0.3733 |
  | 0.9616        | 30.7  | 3500 | 0.2391          | 0.3294 |
  | 0.9303        | 35.09 | 4000 | 0.2352          | 0.3218 |
  | 0.9248        | 39.47 | 4500 | 0.2351          | 0.3207 |
  | 0.8837        | 43.86 | 5000 | 0.2341          | 0.3103 |
  | 0.8887        | 48.25 | 5500 | 0.2311          | 0.3115 |
  | 0.8529        | 52.63 | 6000 | 0.2230          | 0.3001 |
  | 0.8404        | 57.02 | 6500 | 0.2279          | 0.3054 |
  | 0.8242        | 61.4  | 7000 | 0.2298          | 0.3006 |
  | 0.8288        | 65.79 | 7500 | 0.2333          | 0.2997 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  