readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: libri-alpha-0.25-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-0.25-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: 100.6813
  - Wer: 0.1288
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 633.8748      | 0.75  | 100  | 196.0037        | 0.1739 |
  | 464.4784      | 1.49  | 200  | 158.6537        | 0.1839 |
  | 402.8189      | 2.24  | 300  | 133.1326        | 0.1780 |
  | 375.327       | 2.99  | 400  | 124.3412        | 0.1694 |
  | 350.275       | 3.73  | 500  | 119.5099        | 0.1563 |
  | 336.7376      | 4.48  | 600  | 115.2354        | 0.1565 |
  | 322.0894      | 5.22  | 700  | 114.3447        | 0.1480 |
  | 312.4163      | 5.97  | 800  | 112.2822        | 0.1488 |
  | 308.7276      | 6.72  | 900  | 111.4043        | 0.1446 |
  | 305.5383      | 7.46  | 1000 | 109.4352        | 0.1427 |
  | 300.5675      | 8.21  | 1100 | 108.9405        | 0.1397 |
  | 296.3556      | 8.96  | 1200 | 107.5694        | 0.1416 |
  | 294.1826      | 9.7   | 1300 | 106.5605        | 0.1384 |
  | 290.6859      | 10.45 | 1400 | 106.9627        | 0.1365 |
  | 286.1896      | 11.19 | 1500 | 106.2790        | 0.1343 |
  | 282.0118      | 11.94 | 1600 | 105.8356        | 0.1363 |
  | 277.4627      | 12.69 | 1700 | 105.2998        | 0.1354 |
  | 282.7745      | 13.43 | 1800 | 105.2338        | 0.1347 |
  | 275.9889      | 14.18 | 1900 | 104.4767        | 0.1331 |
  | 272.8276      | 14.93 | 2000 | 104.2786        | 0.1346 |
  | 272.7259      | 15.67 | 2100 | 103.5771        | 0.1330 |
  | 267.0375      | 16.42 | 2200 | 102.2268        | 0.1334 |
  | 269.7613      | 17.16 | 2300 | 102.9402        | 0.1316 |
  | 272.2131      | 17.91 | 2400 | 102.2786        | 0.1333 |
  | 269.4063      | 18.66 | 2500 | 101.9838        | 0.1336 |
  | 260.0655      | 19.4  | 2600 | 102.0956        | 0.1305 |
  | 262.16        | 20.15 | 2700 | 101.6337        | 0.1309 |
  | 262.3828      | 20.9  | 2800 | 102.1123        | 0.1302 |
  | 261.6759      | 21.64 | 2900 | 101.4485        | 0.1301 |
  | 264.2934      | 22.39 | 3000 | 101.2778        | 0.1293 |
  | 264.9853      | 23.13 | 3100 | 101.4405        | 0.1298 |
  | 262.5046      | 23.88 | 3200 | 101.3836        | 0.1299 |
  | 263.8816      | 24.63 | 3300 | 101.2221        | 0.1293 |
  | 261.7403      | 25.37 | 3400 | 101.1367        | 0.1280 |
  | 258.1267      | 26.12 | 3500 | 100.7606        | 0.1293 |
  | 255.0854      | 26.87 | 3600 | 100.6364        | 0.1289 |
  | 256.0877      | 27.61 | 3700 | 100.6879        | 0.1287 |
  | 258.1701      | 28.36 | 3800 | 100.6964        | 0.1287 |
  | 256.9546      | 29.1  | 3900 | 100.6813        | 0.1288 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.11.0
  