readme: ---
  language:
  - fa
  tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: common8
    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. -->
  
  # common8
  
  This model is a fine-tuned version of [wghts/checkpoint-20000](https://huggingface.co/wghts/checkpoint-20000) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FA dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3174
  - Wer: 0.3022
  
  ## 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: 1e-06
  - train_batch_size: 32
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 6
  - total_train_batch_size: 192
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - num_epochs: 250.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step  | Validation Loss | Wer    |
  |:-------------:|:------:|:-----:|:---------------:|:------:|
  | 3.5847        | 1.93   | 500   | 3.5104          | 1.0    |
  | 2.7858        | 3.86   | 1000  | 2.9601          | 1.0001 |
  | 1.6827        | 5.79   | 1500  | 0.7853          | 0.7030 |
  | 1.4656        | 7.72   | 2000  | 0.6076          | 0.6014 |
  | 1.3693        | 9.65   | 2500  | 0.5114          | 0.5307 |
  | 1.379         | 11.58  | 3000  | 0.4666          | 0.4940 |
  | 1.2832        | 13.51  | 3500  | 0.4257          | 0.4593 |
  | 1.1931        | 15.44  | 4000  | 0.4039          | 0.4427 |
  | 1.2911        | 17.37  | 4500  | 0.3956          | 0.4295 |
  | 1.1577        | 19.3   | 5000  | 0.3705          | 0.4114 |
  | 1.1135        | 21.24  | 5500  | 0.3740          | 0.4010 |
  | 1.19          | 23.17  | 6000  | 0.3611          | 0.3935 |
  | 1.1008        | 25.1   | 6500  | 0.3503          | 0.3880 |
  | 1.0805        | 27.03  | 7000  | 0.3427          | 0.3781 |
  | 1.1556        | 28.96  | 7500  | 0.3442          | 0.3727 |
  | 1.0596        | 30.89  | 8000  | 0.3398          | 0.3646 |
  | 1.0219        | 32.82  | 8500  | 0.3312          | 0.3660 |
  | 1.1042        | 34.75  | 9000  | 0.3287          | 0.3612 |
  | 1.0273        | 36.68  | 9500  | 0.3236          | 0.3556 |
  | 1.0383        | 38.61  | 10000 | 0.3217          | 0.3558 |
  | 1.0498        | 40.54  | 10500 | 0.3205          | 0.3520 |
  | 0.9969        | 42.47  | 11000 | 0.3125          | 0.3504 |
  | 1.0658        | 44.4   | 11500 | 0.3120          | 0.3493 |
  | 0.992         | 46.33  | 12000 | 0.3137          | 0.3476 |
  | 0.9737        | 48.26  | 12500 | 0.3085          | 0.3413 |
  | 1.0817        | 50.19  | 13000 | 0.3091          | 0.3418 |
  | 0.9414        | 52.12  | 13500 | 0.3072          | 0.3344 |
  | 0.9295        | 54.05  | 14000 | 0.3039          | 0.3322 |
  | 1.0248        | 55.98  | 14500 | 0.2991          | 0.3325 |
  | 0.9474        | 57.91  | 15000 | 0.3032          | 0.3348 |
  | 0.928         | 59.85  | 15500 | 0.2999          | 0.3285 |
  | 1.0321        | 61.78  | 16000 | 0.2982          | 0.3253 |
  | 0.9255        | 63.71  | 16500 | 0.2970          | 0.3231 |
  | 0.8928        | 65.64  | 17000 | 0.2993          | 0.3250 |
  | 1.008         | 67.57  | 17500 | 0.2985          | 0.3222 |
  | 0.9371        | 69.5   | 18000 | 0.2968          | 0.3216 |
  | 0.9077        | 71.43  | 18500 | 0.3011          | 0.3299 |
  | 1.0044        | 73.36  | 19000 | 0.3053          | 0.3306 |
  | 0.9625        | 75.29  | 19500 | 0.3159          | 0.3295 |
  | 0.9816        | 77.22  | 20000 | 0.3080          | 0.3304 |
  | 0.9587        | 119.19 | 20500 | 0.3088          | 0.3284 |
  | 0.9178        | 122.09 | 21000 | 0.3132          | 0.3320 |
  | 1.0282        | 125.0  | 21500 | 0.3099          | 0.3266 |
  | 0.9337        | 127.9  | 22000 | 0.3110          | 0.3317 |
  | 0.8822        | 130.81 | 22500 | 0.3037          | 0.3247 |
  | 0.9644        | 133.72 | 23000 | 0.3037          | 0.3238 |
  | 0.9214        | 136.62 | 23500 | 0.3040          | 0.3234 |
  | 0.9167        | 139.53 | 24000 | 0.3079          | 0.3203 |
  | 0.9047        | 142.44 | 24500 | 0.3018          | 0.3177 |
  | 0.8909        | 145.35 | 25000 | 0.3053          | 0.3181 |
  | 0.9646        | 148.25 | 25500 | 0.3095          | 0.3229 |
  | 0.8802        | 151.16 | 26000 | 0.3111          | 0.3192 |
  | 0.8411        | 154.07 | 26500 | 0.3068          | 0.3123 |
  | 0.9235        | 156.97 | 27000 | 0.3090          | 0.3177 |
  | 0.8943        | 159.88 | 27500 | 0.3115          | 0.3179 |
  | 0.8854        | 162.79 | 28000 | 0.3052          | 0.3157 |
  | 0.8734        | 165.69 | 28500 | 0.3077          | 0.3124 |
  | 0.8515        | 168.6  | 29000 | 0.3117          | 0.3128 |
  | 0.912         | 1