readme: ---
  language:
  - hu
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - hu
  - 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 - Hungarian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: hu
      metrics:
      - name: Test WER
        type: wer
        value: 31.099
      - name: Test CER
        type: cer
        value: 6.737
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: hu
      metrics:
      - name: Test WER
        type: wer
        value: 45.469
      - name: Test CER
        type: cer
        value: 15.727
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: hu
      metrics:
      - name: Test WER
        type: wer
        value: 48.2
  ---
  
  <!-- 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-hungarian
  
  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 - HU dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2562
  - Wer: 0.3112
  
  ## 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: 1000
  - num_epochs: 50.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 2.3964        | 3.52  | 1000  | 1.2251          | 0.8781 |
  | 1.3176        | 7.04  | 2000  | 0.3872          | 0.4462 |
  | 1.1999        | 10.56 | 3000  | 0.3244          | 0.3922 |
  | 1.1633        | 14.08 | 4000  | 0.3014          | 0.3704 |
  | 1.1132        | 17.61 | 5000  | 0.2913          | 0.3623 |
  | 1.0888        | 21.13 | 6000  | 0.2864          | 0.3498 |
  | 1.0487        | 24.65 | 7000  | 0.2821          | 0.3435 |
  | 1.0431        | 28.17 | 8000  | 0.2739          | 0.3308 |
  | 0.9896        | 31.69 | 9000  | 0.2629          | 0.3243 |
  | 0.9839        | 35.21 | 10000 | 0.2806          | 0.3308 |
  | 0.9586        | 38.73 | 11000 | 0.2650          | 0.3235 |
  | 0.9501        | 42.25 | 12000 | 0.2585          | 0.3173 |
  | 0.938         | 45.77 | 13000 | 0.2561          | 0.3117 |
  | 0.921         | 49.3  | 14000 | 0.2559          | 0.3115 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  