readme: ---
  language:
  - hy-AM
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - hy
  datasets:
  - common_voice
  model-index:
  - name: ''
    results: []
  ---
  
  <!-- 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_8_0 - HY-AM dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5891
  - Wer: 0.6569
  
  **Note**: If you aim for best performance use [this model](https://huggingface.co/arampacha/wav2vec2-xls-r-300m-hy). It is trained using noizy student procedure and achieves considerably better results. 
  
  ## 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: 0.0001
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - training_steps: 1200
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 9.167         | 16.67  | 100  | 3.5599          | 1.0    |
  | 3.2645        | 33.33  | 200  | 3.1771          | 1.0    |
  | 3.1509        | 50.0   | 300  | 3.1321          | 1.0    |
  | 3.0757        | 66.67  | 400  | 2.8594          | 1.0    |
  | 2.5274        | 83.33  | 500  | 1.5286          | 0.9797 |
  | 1.6826        | 100.0  | 600  | 0.8058          | 0.7974 |
  | 1.2868        | 116.67 | 700  | 0.6713          | 0.7279 |
  | 1.1262        | 133.33 | 800  | 0.6308          | 0.7034 |
  | 1.0408        | 150.0  | 900  | 0.6056          | 0.6745 |
  | 0.9617        | 166.67 | 1000 | 0.5891          | 0.6569 |
  | 0.9196        | 183.33 | 1100 | 0.5913          | 0.6432 |
  | 0.8853        | 200.0  | 1200 | 0.5924          | 0.6347 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  