readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: model-960hfacebook-2022.06.08
    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. -->
  
  # model-960hfacebook-2022.06.08
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-960h-lv60-self](https://huggingface.co/facebook/wav2vec2-large-960h-lv60-self) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2907
  - Wer: 0.1804
  
  ## 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: 0.0003
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 25
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 6.7634        | 0.21  | 300   | 2.9743          | 0.9998 |
  | 1.6536        | 0.43  | 600   | 0.8605          | 0.7529 |
  | 0.9823        | 0.64  | 900   | 0.6600          | 0.6286 |
  | 0.8708        | 0.86  | 1200  | 0.5780          | 0.5736 |
  | 0.7878        | 1.07  | 1500  | 0.5386          | 0.5326 |
  | 0.7033        | 1.29  | 1800  | 0.4986          | 0.4992 |
  | 0.681         | 1.5   | 2100  | 0.4575          | 0.4778 |
  | 0.6537        | 1.72  | 2400  | 0.4591          | 0.4482 |
  | 0.6263        | 1.93  | 2700  | 0.4317          | 0.4353 |
  | 0.5811        | 2.14  | 3000  | 0.4149          | 0.4159 |
  | 0.5565        | 2.36  | 3300  | 0.4170          | 0.3956 |
  | 0.5501        | 2.57  | 3600  | 0.4007          | 0.3929 |
  | 0.5444        | 2.79  | 3900  | 0.3930          | 0.3851 |
  | 0.5177        | 3.0   | 4200  | 0.4006          | 0.3630 |
  | 0.4682        | 3.22  | 4500  | 0.3707          | 0.3713 |
  | 0.4805        | 3.43  | 4800  | 0.3564          | 0.3583 |
  | 0.4715        | 3.65  | 5100  | 0.3596          | 0.3434 |
  | 0.4482        | 3.86  | 5400  | 0.3555          | 0.3394 |
  | 0.4407        | 4.07  | 5700  | 0.3680          | 0.3312 |
  | 0.4134        | 4.29  | 6000  | 0.3534          | 0.3328 |
  | 0.4165        | 4.5   | 6300  | 0.3294          | 0.3259 |
  | 0.4196        | 4.72  | 6600  | 0.3353          | 0.3214 |
  | 0.4117        | 4.93  | 6900  | 0.3266          | 0.3211 |
  | 0.3847        | 5.15  | 7200  | 0.3365          | 0.3156 |
  | 0.3687        | 5.36  | 7500  | 0.3233          | 0.3014 |
  | 0.376         | 5.58  | 7800  | 0.3345          | 0.2979 |
  | 0.3732        | 5.79  | 8100  | 0.3105          | 0.2882 |
  | 0.3705        | 6.0   | 8400  | 0.3252          | 0.2935 |
  | 0.3311        | 6.22  | 8700  | 0.3266          | 0.2911 |
  | 0.3386        | 6.43  | 9000  | 0.2975          | 0.2765 |
  | 0.337         | 6.65  | 9300  | 0.3070          | 0.2826 |
  | 0.3458        | 6.86  | 9600  | 0.3090          | 0.2766 |
  | 0.3218        | 7.08  | 9900  | 0.3117          | 0.2748 |
  | 0.3041        | 7.29  | 10200 | 0.2989          | 0.2651 |
  | 0.3031        | 7.51  | 10500 | 0.3210          | 0.2672 |
  | 0.3037        | 7.72  | 10800 | 0.3040          | 0.2667 |
  | 0.3126        | 7.93  | 11100 | 0.2867          | 0.2613 |
  | 0.3005        | 8.15  | 11400 | 0.3075          | 0.2610 |
  | 0.2802        | 8.36  | 11700 | 0.3129          | 0.2608 |
  | 0.2785        | 8.58  | 12000 | 0.3002          | 0.2579 |
  | 0.2788        | 8.79  | 12300 | 0.3063          | 0.2476 |
  | 0.286         | 9.01  | 12600 | 0.2971          | 0.2495 |
  | 0.2534        | 9.22  | 12900 | 0.2766          | 0.2452 |
  | 0.2542        | 9.44  | 13200 | 0.2893          | 0.2405 |
  | 0.2576        | 9.65  | 13500 | 0.3038          | 0.2518 |
  | 0.2552        | 9.86  | 13800 | 0.2851          | 0.2429 |
  | 0.2487        | 10.08 | 14100 | 0.2858          | 0.2356 |
  | 0.2441        | 10.29 | 14400 | 0.2999          | 0.2364 |
  | 0.2345        | 10.51 | 14700 | 0.2907          | 0.2373 |
  | 0.2352        | 10.72 | 15000 | 0.2885          | 0.2402 |
  | 0.2464        | 10.94 | 15300 | 0.2896          | 0.2339 |
  | 0.2219        | 11.15 | 15600 | 0.2999          | 0.2351 |
  | 0.2257        | 11.37 | 15900 | 0.2930          | 0.2326 |
  | 0.2184        | 11.58 | 16200 | 0.2980          | 0.2353 |
  | 0.2182        | 11.79 | 16500 | 0.2832          | 0.2296 |
  | 0.2224        | 12.01 | 16800 | 0.2797          | 0.2285 |
  | 0.1991        | 12.22 | 17100 | 0.2810          | 0.2296 |
  | 0.1993        | 12.44 | 17400 | 0.2949          | 0.2253 |
  | 0.2042        | 12.65 | 17700 | 0.2864          | 0.2207 |
  | 0.2083        | 12.87 | 18000 | 0.286