readme: ---
  language:
  - bg
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - bg
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: XLS-R-300M - Bulgarian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: bg
      metrics:
      - name: Test WER
        type: wer
        value: 46.68
      - name: Test CER
        type: cer
        value: 10.75
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: bg
      metrics:
      - name: Test WER
        type: wer
        value: 63.68
      - name: Test CER
        type: cer
        value: 19.88
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: bg
      metrics:
      - name: Test WER
        type: wer
        value: 64.08
  ---
  
  <!-- 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-bulgarian
  
  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 - BG dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4487
  - Wer: 0.4674
  
  ## 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: 100.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 2.9774        | 6.33  | 500  | 2.9769          | 1.0    |
  | 1.3453        | 12.66 | 1000 | 0.6523          | 0.6980 |
  | 1.1658        | 18.99 | 1500 | 0.5636          | 0.6359 |
  | 1.0797        | 25.32 | 2000 | 0.5004          | 0.5759 |
  | 1.044         | 31.65 | 2500 | 0.4958          | 0.5569 |
  | 0.9915        | 37.97 | 3000 | 0.4971          | 0.5350 |
  | 0.9429        | 44.3  | 3500 | 0.4829          | 0.5229 |
  | 0.9266        | 50.63 | 4000 | 0.4515          | 0.5074 |
  | 0.8965        | 56.96 | 4500 | 0.4599          | 0.5039 |
  | 0.878         | 63.29 | 5000 | 0.4735          | 0.4954 |
  | 0.8494        | 69.62 | 5500 | 0.4460          | 0.4878 |
  | 0.8343        | 75.95 | 6000 | 0.4510          | 0.4795 |
  | 0.8236        | 82.28 | 6500 | 0.4538          | 0.4789 |
  | 0.8069        | 88.61 | 7000 | 0.4526          | 0.4748 |
  | 0.7958        | 94.94 | 7500 | 0.4496          | 0.4700 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  