readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: stt-v11-medium
    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. -->
  
  # stt-v11-medium
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3701
  - Wer: 0.2216
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 271
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer    |
  |:-------------:|:------:|:----:|:---------------:|:------:|
  | 2.8041        | 14.28  | 500  | 0.3662          | 0.4315 |
  | 0.3702        | 28.56  | 1000 | 0.3102          | 0.2966 |
  | 0.1978        | 42.85  | 1500 | 0.3378          | 0.2794 |
  | 0.1467        | 57.14  | 2000 | 0.3201          | 0.2808 |
  | 0.1144        | 71.42  | 2500 | 0.3646          | 0.2698 |
  | 0.0969        | 85.7   | 3000 | 0.3234          | 0.2657 |
  | 0.0832        | 99.99  | 3500 | 0.3744          | 0.2712 |
  | 0.0732        | 114.28 | 4000 | 0.3217          | 0.2602 |
  | 0.0635        | 128.56 | 4500 | 0.3419          | 0.2491 |
  | 0.0561        | 142.85 | 5000 | 0.3628          | 0.2560 |
  | 0.0491        | 157.14 | 5500 | 0.3458          | 0.2436 |
  | 0.0439        | 171.42 | 6000 | 0.3615          | 0.2519 |
  | 0.0397        | 185.7  | 6500 | 0.3610          | 0.2519 |
  | 0.0352        | 199.99 | 7000 | 0.3514          | 0.2374 |
  | 0.0314        | 214.28 | 7500 | 0.3469          | 0.2450 |
  | 0.0272        | 228.56 | 8000 | 0.3615          | 0.2271 |
  | 0.0247        | 242.85 | 8500 | 0.3614          | 0.2292 |
  | 0.022         | 257.14 | 9000 | 0.3701          | 0.2216 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  