readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: libri-smallw2v2-no-copy-kl-alpha-0.75-T-1-take-3
    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. -->
  
  # libri-smallw2v2-no-copy-kl-alpha-0.75-T-1-take-3
  
  This model was trained from scratch on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 233.4488
  - Wer: 0.3266
  
  ## 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: 0.0002
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.2
  - num_epochs: 100
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 344.6087      | 1.12  | 400   | 259.4728        | 0.4553 |
  | 331.2433      | 2.24  | 800   | 249.7617        | 0.4505 |
  | 324.318       | 3.36  | 1200  | 243.3380        | 0.4476 |
  | 318.8272      | 4.48  | 1600  | 245.5005        | 0.4397 |
  | 314.193       | 5.6   | 2000  | 245.8428        | 0.4389 |
  | 310.3951      | 6.72  | 2400  | 249.0932        | 0.4358 |
  | 307.6068      | 7.84  | 2800  | 248.7932        | 0.4386 |
  | 308.3191      | 8.96  | 3200  | 242.1969        | 0.4309 |
  | 302.0043      | 10.08 | 3600  | 251.7498        | 0.4271 |
  | 296.6045      | 11.2  | 4000  | 246.3982        | 0.4272 |
  | 295.0746      | 12.32 | 4400  | 249.5031        | 0.4201 |
  | 294.2732      | 13.45 | 4800  | 247.5096        | 0.4167 |
  | 290.1665      | 14.57 | 5200  | 247.6531        | 0.4227 |
  | 293.2169      | 15.69 | 5600  | 246.6296        | 0.4150 |
  | 287.6487      | 16.81 | 6000  | 244.2763        | 0.4132 |
  | 287.8109      | 17.93 | 6400  | 243.7672        | 0.4116 |
  | 282.7126      | 19.05 | 6800  | 241.8889        | 0.4073 |
  | 280.5111      | 20.17 | 7200  | 251.7473        | 0.4015 |
  | 276.0679      | 21.29 | 7600  | 242.1010        | 0.3990 |
  | 275.7184      | 22.41 | 8000  | 244.3330        | 0.3966 |
  | 273.0371      | 23.53 | 8400  | 240.5063        | 0.3908 |
  | 268.2875      | 24.65 | 8800  | 241.2827        | 0.3916 |
  | 262.7938      | 25.77 | 9200  | 236.9669        | 0.3870 |
  | 262.0252      | 26.89 | 9600  | 238.0447        | 0.3837 |
  | 256.3527      | 28.01 | 10000 | 231.9627        | 0.3777 |
  | 253.4488      | 29.13 | 10400 | 241.3886        | 0.3778 |
  | 251.0047      | 30.25 | 10800 | 239.3254        | 0.3716 |
  | 247.1357      | 31.37 | 11200 | 234.5317        | 0.3743 |
  | 245.7466      | 32.49 | 11600 | 237.2660        | 0.3732 |
  | 240.7763      | 33.61 | 12000 | 234.2133        | 0.3719 |
  | 240.4568      | 34.73 | 12400 | 233.6447        | 0.3652 |
  | 236.5008      | 35.85 | 12800 | 231.5317        | 0.3634 |
  | 234.3844      | 36.97 | 13200 | 235.9599        | 0.3667 |
  | 234.8658      | 38.1  | 13600 | 235.8033        | 0.3629 |
  | 229.0455      | 39.22 | 14000 | 235.2613        | 0.3597 |
  | 228.1712      | 40.34 | 14400 | 237.7952        | 0.3559 |
  | 225.4442      | 41.46 | 14800 | 237.6732        | 0.3553 |
  | 223.492       | 42.58 | 15200 | 228.6896        | 0.3549 |
  | 222.2095      | 43.7  | 15600 | 233.7846        | 0.3528 |
  | 221.3752      | 44.82 | 16000 | 235.6401        | 0.3503 |
  | 220.0048      | 45.94 | 16400 | 236.2913        | 0.3486 |
  | 214.734       | 47.06 | 16800 | 233.7592        | 0.3452 |
  | 213.6554      | 48.18 | 17200 | 233.3319        | 0.3468 |
  | 212.7388      | 49.3  | 17600 | 232.7798        | 0.3447 |
  | 210.9421      | 50.42 | 18000 | 239.8152        | 0.3483 |
  | 211.6293      | 51.54 | 18400 | 235.0050        | 0.3450 |
  | 209.8978      | 52.66 | 18800 | 235.3156        | 0.3453 |
  | 207.996       | 53.78 | 19200 | 233.3227        | 0.3429 |
  | 206.4369      | 54.9  | 19600 | 231.2948        | 0.3395 |
  | 202.3726      | 56.02 | 20000 | 226.5554        | 0.3387 |
  | 201.5557      | 57.14 | 20400 | 236.6525        | 0.3413 |
  | 203.2557      | 58.26 | 20800 | 231.1979        | 0.3387 |
  | 200.6613      | 59.38 | 21200 | 232.5989        | 0.3361 |
  | 199.9518      | 60.5  | 21600 | 233.6743        | 0.3368 |
  | 198.7427      | 61.62 | 22000 | 236.3777        | 0.3365 |
  | 195.5101      | 62.75 | 22400 | 230.0184        | 0.3354 |
  | 195.4992      | 63.87 | 22800 | 229.9954        | 0.3332 |
  | 193.023       | 64.99 | 23200 | 233.4538        | 0.3343 |
  | 195.5294      | 66.11 | 23600 | 235.9190        | 0.3328 |
  | 193.4176      | 67.23 | 24000 | 235.0465        | 0.3316 |
  | 191.4303      | 68.35 | 24400 | 234.2414        | 0.3331 |
  | 190.1889      | 