readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: libri-smallw2v2-no-copy-mse-alpha-0.75-T-1
    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-mse-alpha-0.75-T-1
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 299.5353
  - Wer: 0.5607
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 2621.6909     | 1.79  | 400   | 892.3344        | 1.0000 |
  | 1182.3671     | 3.59  | 800   | 583.0377        | 0.9766 |
  | 946.8591      | 5.38  | 1200  | 493.0189        | 0.9365 |
  | 833.3073      | 7.17  | 1600  | 444.2031        | 0.9141 |
  | 751.816       | 8.97  | 2000  | 400.5189        | 0.8937 |
  | 698.0563      | 10.76 | 2400  | 369.2302        | 0.8649 |
  | 644.5172      | 12.56 | 2800  | 345.4725        | 0.8458 |
  | 600.5121      | 14.35 | 3200  | 323.2295        | 0.8151 |
  | 561.2316      | 16.14 | 3600  | 307.8979        | 0.7950 |
  | 523.6023      | 17.94 | 4000  | 291.1282        | 0.7720 |
  | 496.2595      | 19.73 | 4400  | 279.5770        | 0.7517 |
  | 466.5839      | 21.52 | 4800  | 267.7692        | 0.7263 |
  | 440.6372      | 23.32 | 5200  | 258.0482        | 0.7028 |
  | 417.6962      | 25.11 | 5600  | 254.2653        | 0.6902 |
  | 392.6432      | 26.91 | 6000  | 252.7504        | 0.6774 |
  | 378.9874      | 28.7  | 6400  | 246.1504        | 0.6714 |
  | 361.5383      | 30.49 | 6800  | 243.2339        | 0.6630 |
  | 345.9527      | 32.29 | 7200  | 242.4769        | 0.6494 |
  | 335.28        | 34.08 | 7600  | 243.5441        | 0.6448 |
  | 320.2823      | 35.87 | 8000  | 242.6982        | 0.6353 |
  | 306.8673      | 37.67 | 8400  | 252.8057        | 0.6280 |
  | 300.3173      | 39.46 | 8800  | 249.5198        | 0.6267 |
  | 290.0972      | 41.26 | 9200  | 243.8252        | 0.6218 |
  | 283.0466      | 43.05 | 9600  | 242.9062        | 0.6173 |
  | 273.4801      | 44.84 | 10000 | 249.2953        | 0.6121 |
  | 264.7652      | 46.64 | 10400 | 251.2528        | 0.6127 |
  | 257.2499      | 48.43 | 10800 | 257.1318        | 0.6089 |
  | 250.4637      | 50.22 | 11200 | 264.7531        | 0.6069 |
  | 245.2013      | 52.02 | 11600 | 258.1169        | 0.6000 |
  | 240.3053      | 53.81 | 12000 | 255.6198        | 0.5941 |
  | 232.0262      | 55.61 | 12400 | 261.2134        | 0.5949 |
  | 228.3372      | 57.4  | 12800 | 263.1902        | 0.5919 |
  | 222.2224      | 59.19 | 13200 | 271.1831        | 0.5898 |
  | 218.0379      | 60.99 | 13600 | 264.8538        | 0.5821 |
  | 215.7583      | 62.78 | 14000 | 268.3278        | 0.5874 |
  | 210.5649      | 64.57 | 14400 | 273.0802        | 0.5808 |
  | 205.7684      | 66.37 | 14800 | 273.7237        | 0.5792 |
  | 202.7417      | 68.16 | 15200 | 276.0477        | 0.5750 |
  | 197.5293      | 69.96 | 15600 | 272.9896        | 0.5785 |
  | 196.512       | 71.75 | 16000 | 274.7004        | 0.5777 |
  | 193.9167      | 73.54 | 16400 | 275.8243        | 0.5727 |
  | 190.2722      | 75.34 | 16800 | 283.2336        | 0.5743 |
  | 187.5092      | 77.13 | 17200 | 284.5899        | 0.5723 |
  | 182.8259      | 78.92 | 17600 | 287.1284        | 0.5732 |
  | 184.1322      | 80.72 | 18000 | 285.4507        | 0.5704 |
  | 180.0438      | 82.51 | 18400 | 283.7040        | 0.5684 |
  | 179.6387      | 84.3  | 18800 | 288.0453        | 0.5670 |
  | 176.7927      | 86.1  | 19200 | 290.4306        | 0.5662 |
  | 173.8417      | 87.89 | 19600 | 298.6391        | 0.5663 |
  | 174.4995      | 89.69 | 20000 | 299.5260        | 0.5634 |
  | 171.9799      | 91.48 | 20400 | 301.1923        | 0.5653 |
  | 170.4011      | 93.27 | 20800 | 299.7171        | 0.5667 |
  | 170.4423      | 95.07 | 21200 | 296.5629        | 0.5639 |
  | 169.7396      | 96.86 | 21600 | 299.2657        | 0.5622 |
  | 166.9574      | 98.65 | 22000 | 299.5353        | 0.5607 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  