readme: ---
  language:
  - cs
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - cs
  - generated_from_trainer
  - hf-asr-leaderboard
  - model_for_talk
  - mozilla-foundation/common_voice_8_0
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_8_0
  model-index:
  - name: sammy786/wav2vec2-xlsr-czech
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: cs
      metrics:
      - name: Test WER
        type: wer
        value: 11.22
      - name: Test CER
        type: cer
        value: 2.52
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: cs
      metrics:
      - name: Test WER
        type: wer
        value: 97.02
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: cs
      metrics:
      - name: Test WER
        type: wer
        value: 69.7
  ---
  # sammy786/wav2vec2-xlsr-czech
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - cs dataset.
  It achieves the following results on evaluation set (which is 10 percent of train data set merged with other and dev datasets):
  - Loss: 7.26
  - Wer: 19.32
  
  ## Model description
  "facebook/wav2vec2-xls-r-1b" was finetuned.
  
  ## Intended uses & limitations
  More information needed
  ## Training and evaluation data
  Training data - 
  Common voice Finnish train.tsv, dev.tsv, invalidated.tsv and other.tsv
  
  ## Training procedure
  For creating the train dataset, all possible datasets were appended and 90-10 split was used. 
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  
  - learning_rate: 0.000045637994662983496
  - train_batch_size: 8
  - eval_batch_size: 16
  - seed: 13
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine_with_restarts
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 7
  - mixed_precision_training: Native AMP
  
  
  ### Training results
  
  | Step | Training Loss | Validation Loss | Wer      |
  |:----:|:-------------:|:---------------:|:--------:|
  | 200  | 6.654600      | 3.329486        | 1.000000 |
  | 400  | 1.700600      | 0.317266        | 0.409446 |
  | 600  | 0.767400      | 0.211371        | 0.313981 |
  | 800  | 0.718600      | 0.167771        | 0.280676 |
  | 1000 | 0.661700      | 0.142229        | 0.258938 |
  | 1200 | 0.594400      | 0.137321        | 0.256275 |
  | 1400 | 0.583900      | 0.132922        | 0.248418 |
  | 1600 | 0.565100      | 0.117214        | 0.238640 |
  | 1800 | 0.369600      | 0.116954        | 0.238291 |
  | 2000 | 0.292800      | 0.109973        | 0.227509 |
  | 2200 | 0.255400      | 0.104955        | 0.228120 |
  | 2400 | 0.266800      | 0.097268        | 0.220525 |
  | 2600 | 0.232700      | 0.096055        | 0.213584 |
  | 2800 | 0.213700      | 0.097770        | 0.218866 |
  | 3000 | 0.209900      | 0.091633        | 0.210485 |
  | 3200 | 0.196800      | 0.090342        | 0.208739 |
  | 3400 | 0.200500      | 0.082326        | 0.204767 |
  | 3600 | 0.176800      | 0.085491        | 0.204068 |
  | 3800 | 0.170000      | 0.081289        | 0.201231 |
  | 4000 | 0.166200      | 0.080762        | 0.200227 |
  | 4200 | 0.161700      | 0.076671        | 0.198001 |
  | 4400 | 0.147000      | 0.077383        | 0.196997 |
  | 4600 | 0.141900      | 0.076057        | 0.195862 |
  | 4800 | 0.144800      | 0.074612        | 0.195120 |
  | 5000 | 0.138900      | 0.073138        | 0.193985 |
  | 5200 | 0.143900      | 0.072802        | 0.192894 |
  | 5400 | 0.131100      | 0.072764        | 0.193723 |
  | 5600 | 0.137000      | 0.072697        | 0.193679 |
  | 5800 | 0.133300      | 0.072651        | 0.193286 |
  
  
  ### Framework versions
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.0+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.10.3
  
  #### Evaluation Commands
  
  1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`
  
  ```bash
  python eval.py --model_id sammy786/wav2vec2-xlsr-czech --dataset mozilla-foundation/common_voice_8_0 --config cs --split test
  ```