readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: libri-alpha-0.5-Temp-1-processor-change
    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-alpha-0.5-Temp-1-processor-change
  
  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: 91.9750
  - Wer: 0.1187
  
  ## 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: 2e-05
  - 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_steps: 500
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 569.0646      | 0.75  | 100  | 175.3549        | 0.1589 |
  | 440.3574      | 1.49  | 200  | 146.3654        | 0.1640 |
  | 398.2328      | 2.24  | 300  | 128.7082        | 0.1562 |
  | 357.5816      | 2.99  | 400  | 117.7871        | 0.1495 |
  | 344.3317      | 3.73  | 500  | 111.0376        | 0.1417 |
  | 331.0486      | 4.48  | 600  | 106.5447        | 0.1398 |
  | 321.4498      | 5.22  | 700  | 105.1187        | 0.1363 |
  | 305.8177      | 5.97  | 800  | 103.2541        | 0.1365 |
  | 304.2076      | 6.72  | 900  | 105.3060        | 0.1385 |
  | 297.746       | 7.46  | 1000 | 101.1069        | 0.1307 |
  | 285.7675      | 8.21  | 1100 | 99.9853         | 0.1303 |
  | 284.6546      | 8.96  | 1200 | 98.5235         | 0.1292 |
  | 281.672       | 9.7   | 1300 | 97.8004         | 0.1295 |
  | 281.0029      | 10.45 | 1400 | 96.9385         | 0.1278 |
  | 283.847       | 11.19 | 1500 | 96.3700         | 0.1275 |
  | 274.4053      | 11.94 | 1600 | 95.9557         | 0.1281 |
  | 271.8855      | 12.69 | 1700 | 95.5764         | 0.1250 |
  | 275.416       | 13.43 | 1800 | 95.0451         | 0.1266 |
  | 267.7354      | 14.18 | 1900 | 94.6620         | 0.1242 |
  | 273.9816      | 14.93 | 2000 | 95.0889         | 0.1241 |
  | 263.9812      | 15.67 | 2100 | 94.4231         | 0.1241 |
  | 258.6033      | 16.42 | 2200 | 93.8011         | 0.1225 |
  | 260.4275      | 17.16 | 2300 | 94.0336         | 0.1210 |
  | 258.7905      | 17.91 | 2400 | 93.4633         | 0.1216 |
  | 255.6817      | 18.66 | 2500 | 93.0448         | 0.1212 |
  | 252.3298      | 19.4  | 2600 | 92.9945         | 0.1216 |
  | 250.5598      | 20.15 | 2700 | 92.9767         | 0.1200 |
  | 249.4384      | 20.9  | 2800 | 93.1555         | 0.1203 |
  | 255.6291      | 21.64 | 2900 | 92.7784         | 0.1208 |
  | 249.5222      | 22.39 | 3000 | 92.5792         | 0.1203 |
  | 250.498       | 23.13 | 3100 | 92.4570         | 0.1205 |
  | 252.2656      | 23.88 | 3200 | 92.3685         | 0.1199 |
  | 248.1438      | 24.63 | 3300 | 92.3731         | 0.1198 |
  | 240.2946      | 25.37 | 3400 | 92.1875         | 0.1192 |
  | 256.2254      | 26.12 | 3500 | 91.9586         | 0.1192 |
  | 248.603       | 26.87 | 3600 | 91.9599         | 0.1191 |
  | 252.9337      | 27.61 | 3700 | 92.1080         | 0.1189 |
  | 250.9757      | 28.36 | 3800 | 92.1051         | 0.1188 |
  | 248.7415      | 29.1  | 3900 | 91.9927         | 0.1187 |
  | 248.7394      | 29.85 | 4000 | 91.9750         | 0.1187 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.11.0
  