readme: ---
  language:
  - uz
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_10_0
  - generated_from_trainer
  datasets:
  - common_voice_10_0
  model-index:
  - name: xls-r-uzbek-cv10
    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. -->
  
  # xls-r-uzbek-cv10
  
  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_10_0 - UZ dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2491
  - Wer: 0.2588
  - Cer: 0.0513
  
  ## 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: 3e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 32
  - 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  | Cer    | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:------:|:---------------:|:------:|
  | 3.1215        | 0.68  | 500   | 1.0    | 3.1188          | 1.0    |
  | 2.8562        | 1.36  | 1000  | 0.9689 | 2.5724          | 1.0002 |
  | 1.2709        | 2.04  | 1500  | 0.1471 | 0.6278          | 0.6478 |
  | 1.0817        | 2.72  | 2000  | 0.1304 | 0.4989          | 0.5931 |
  | 0.9801        | 3.4   | 2500  | 0.1225 | 0.4582          | 0.5667 |
  | 0.951         | 4.08  | 3000  | 0.1149 | 0.4239          | 0.5381 |
  | 0.8834        | 4.76  | 3500  | 0.1092 | 0.4016          | 0.5158 |
  | 0.857         | 5.44  | 4000  | 0.1047 | 0.3785          | 0.4992 |
  | 0.8307        | 6.12  | 4500  | 0.1004 | 0.3720          | 0.4811 |
  | 0.805         | 6.8   | 5000  | 0.0937 | 0.3450          | 0.4537 |
  | 0.7828        | 7.48  | 5500  | 0.0912 | 0.3421          | 0.4460 |
  | 0.7789        | 8.16  | 6000  | 0.0890 | 0.3295          | 0.4337 |
  | 0.755         | 8.84  | 6500  | 0.0862 | 0.3257          | 0.4222 |
  | 0.7464        | 9.52  | 7000  | 0.0847 | 0.3269          | 0.4155 |
  | 0.7293        | 10.2  | 7500  | 0.0823 | 0.3121          | 0.4025 |
  | 0.7283        | 10.88 | 8000  | 0.0789 | 0.2991          | 0.3941 |
  | 0.7145        | 11.56 | 8500  | 0.0786 | 0.2961          | 0.3868 |
  | 0.6963        | 12.24 | 9000  | 0.0767 | 0.2972          | 0.3784 |
  | 0.6981        | 12.92 | 9500  | 0.0757 | 0.2880          | 0.3750 |
  | 0.6888        | 13.6  | 10000 | 0.0745 | 0.2865          | 0.3703 |
  | 0.6733        | 14.29 | 10500 | 0.0744 | 0.2887          | 0.3663 |
  | 0.6701        | 14.97 | 11000 | 0.0735 | 0.2857          | 0.3624 |
  | 0.6634        | 15.65 | 11500 | 0.0723 | 0.2822          | 0.3581 |
  | 0.6484        | 16.33 | 12000 | 0.0706 | 0.2778          | 0.3503 |
  | 0.6626        | 17.01 | 12500 | 0.0697 | 0.2697          | 0.3477 |
  | 0.6341        | 17.69 | 13000 | 0.0708 | 0.2804          | 0.3511 |
  | 0.6402        | 18.37 | 13500 | 0.0681 | 0.2665          | 0.3418 |
  | 0.6343        | 19.05 | 14000 | 0.0687 | 0.2748          | 0.3425 |
  | 0.6383        | 19.73 | 14500 | 0.0677 | 0.2696          | 0.3383 |
  | 0.6178        | 20.41 | 15000 | 0.0690 | 0.2743          | 0.3417 |
  | 0.6097        | 21.09 | 15500 | 0.0671 | 0.2663          | 0.3352 |
  | 0.6245        | 21.77 | 16000 | 0.0665 | 0.2685          | 0.3318 |
  | 0.6137        | 22.45 | 16500 | 0.0655 | 0.2700          | 0.3262 |
  | 0.6018        | 23.13 | 17000 | 0.0652 | 0.2657          | 0.3225 |
  | 0.6063        | 23.81 | 17500 | 0.0663 | 0.2664          | 0.3276 |
  | 0.5917        | 24.49 | 18000 | 0.0658 | 0.2725          | 0.3264 |
  | 0.5984        | 25.17 | 18500 | 0.0643 | 0.2593          | 0.3197 |
  | 0.5949        | 25.85 | 19000 | 0.0635 | 0.2581          | 0.3161 |
  | 0.5863        | 26.53 | 19500 | 0.0639 | 0.2543          | 0.3196 |
  | 0.5858        | 27.21 | 20000 | 0.0628 | 0.2620          | 0.3136 |
  | 0.5902        | 27.89 | 20500 | 0.0627 | 0.2549          | 0.3157 |
  | 0.5794        | 28.57 | 21000 | 0.0624 | 0.2543          | 0.3136 |
  | 0.5744        | 29.25 | 21500 | 0.0620 | 0.2542          | 0.3091 |
  | 0.5899        | 29.93 | 22000 | 0.0624 | 0.2540          | 0.3122 |
  | 0.5597        | 30.61 | 22500 | 0.0609 | 0.2500          | 0.3057 |
  | 0.5595        | 31.29 | 23000 | 0.0616 | 0.2539          | 0.3087 |
  | 0.5664        | 31.97 | 23500 | 0.0610 | 0.2504          | 0.3070 |
  | 0.5608        | 32.65 | 24000 | 0.0611 | 0.2535          | 0.3066 |
  | 0.5557        | 33.33 | 24500 | 0.0608 | 0.2538          | 0.3047 |
  | 0.5741        | 34.01 | 25000 | 0.0596 | 0.2480          | 0.3009 |
  | 0.5614        | 34.69 | 25500