readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: 20220517-150219
    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. -->
  
  # 20220517-150219
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2426
  - Wer: 0.2344
  - Cer: 0.0434
  
  ## 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: 4
  - eval_batch_size: 8
  - seed: 1339
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - num_epochs: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
  | 5.3867        | 0.02  | 200   | 3.2171          | 1.0    | 1.0    |
  | 3.1288        | 0.04  | 400   | 2.9394          | 1.0    | 1.0    |
  | 1.8298        | 0.06  | 600   | 0.9138          | 0.8416 | 0.2039 |
  | 0.9751        | 0.07  | 800   | 0.6568          | 0.6928 | 0.1566 |
  | 0.7934        | 0.09  | 1000  | 0.5314          | 0.6225 | 0.1277 |
  | 0.663         | 0.11  | 1200  | 0.4759          | 0.5730 | 0.1174 |
  | 0.617         | 0.13  | 1400  | 0.4515          | 0.5578 | 0.1118 |
  | 0.5473        | 0.15  | 1600  | 0.4017          | 0.5157 | 0.1004 |
  | 0.5283        | 0.17  | 1800  | 0.3872          | 0.5094 | 0.0982 |
  | 0.4893        | 0.18  | 2000  | 0.3725          | 0.4860 | 0.0932 |
  | 0.495         | 0.2   | 2200  | 0.3580          | 0.4542 | 0.0878 |
  | 0.4438        | 0.22  | 2400  | 0.3443          | 0.4366 | 0.0858 |
  | 0.4425        | 0.24  | 2600  | 0.3428          | 0.4284 | 0.0865 |
  | 0.4293        | 0.26  | 2800  | 0.3329          | 0.4221 | 0.0819 |
  | 0.3779        | 0.28  | 3000  | 0.3278          | 0.4146 | 0.0794 |
  | 0.4116        | 0.29  | 3200  | 0.3242          | 0.4107 | 0.0757 |
  | 0.3912        | 0.31  | 3400  | 0.3217          | 0.4040 | 0.0776 |
  | 0.391         | 0.33  | 3600  | 0.3127          | 0.3955 | 0.0764 |
  | 0.3696        | 0.35  | 3800  | 0.3153          | 0.3892 | 0.0748 |
  | 0.3576        | 0.37  | 4000  | 0.3156          | 0.3846 | 0.0737 |
  | 0.3553        | 0.39  | 4200  | 0.3024          | 0.3814 | 0.0726 |
  | 0.3394        | 0.4   | 4400  | 0.3022          | 0.3637 | 0.0685 |
  | 0.3345        | 0.42  | 4600  | 0.3130          | 0.3641 | 0.0698 |
  | 0.3357        | 0.44  | 4800  | 0.2913          | 0.3602 | 0.0701 |
  | 0.3411        | 0.46  | 5000  | 0.2941          | 0.3514 | 0.0674 |
  | 0.3031        | 0.48  | 5200  | 0.3043          | 0.3613 | 0.0685 |
  | 0.3305        | 0.5   | 5400  | 0.2967          | 0.3468 | 0.0657 |
  | 0.3004        | 0.51  | 5600  | 0.2723          | 0.3309 | 0.0616 |
  | 0.31          | 0.53  | 5800  | 0.2835          | 0.3404 | 0.0648 |
  | 0.3224        | 0.55  | 6000  | 0.2743          | 0.3358 | 0.0622 |
  | 0.3261        | 0.57  | 6200  | 0.2803          | 0.3358 | 0.0620 |
  | 0.305         | 0.59  | 6400  | 0.2835          | 0.3397 | 0.0629 |
  | 0.3025        | 0.61  | 6600  | 0.2684          | 0.3340 | 0.0639 |
  | 0.2952        | 0.62  | 6800  | 0.2654          | 0.3256 | 0.0617 |
  | 0.2903        | 0.64  | 7000  | 0.2588          | 0.3174 | 0.0596 |
  | 0.2907        | 0.66  | 7200  | 0.2789          | 0.3256 | 0.0623 |
  | 0.2887        | 0.68  | 7400  | 0.2634          | 0.3142 | 0.0605 |
  | 0.291         | 0.7   | 7600  | 0.2644          | 0.3097 | 0.0582 |
  | 0.2646        | 0.72  | 7800  | 0.2753          | 0.3089 | 0.0582 |
  | 0.2683        | 0.73  | 8000  | 0.2703          | 0.3036 | 0.0574 |
  | 0.2808        | 0.75  | 8200  | 0.2544          | 0.2994 | 0.0561 |
  | 0.2724        | 0.77  | 8400  | 0.2584          | 0.3051 | 0.0592 |
  | 0.2516        | 0.79  | 8600  | 0.2575          | 0.2959 | 0.0557 |
  | 0.2561        | 0.81  | 8800  | 0.2594          | 0.2945 | 0.0552 |
  | 0.264         | 0.83  | 9000  | 0.2607          | 0.2987 | 0.0552 |
  | 0.2383        | 0.84  | 9200  | 0.2641          | 0.2983 | 0.0546 |
  | 0.2548        | 0.86  | 9400  | 0.2714          | 0.2930 | 0.0538 |
  | 0.2284        | 0.88  | 9600  | 0.2542          | 0.2945 | 0.0555 |
  | 0.2354        | 0.9   | 9800  | 0.2564          | 0.2937 | 0.0551 |
  | 0.2624        | 0.92  | 10000 | 0.2466          | 0.2891 | 0.0542 |
  | 0.24          | 0.94  | 10200 | 0.2404          | 0.2895 | 0.0528 |
  | 0.2372        | 0.95  | 10400 | 0.2590          | 0.2782 | 0.0518 |
  | 0.2357        | 0.97  | 10600 | 0.2629          | 0.2867 | 0.0531 |
  | 0.2439        | 0.99  | 10800 | 0.2722          | 0.2902 | 0.0556 |
  | 0.220