readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: libri-alpha-0.75-Temp-1-mse
    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-0.75-Temp-1-mse
  
  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: 40.9574
  - Wer: 0.1140
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 314.2983      | 0.75  | 100  | 73.1996         | 0.1509 |
  | 254.3135      | 1.49  | 200  | 61.7104         | 0.1436 |
  | 238.1834      | 2.24  | 300  | 53.4787         | 0.1426 |
  | 212.833       | 2.99  | 400  | 51.2417         | 0.1390 |
  | 202.8803      | 3.73  | 500  | 48.4136         | 0.1323 |
  | 191.6817      | 4.48  | 600  | 45.9843         | 0.1288 |
  | 178.3099      | 5.22  | 700  | 44.9262         | 0.1264 |
  | 176.7728      | 5.97  | 800  | 44.0379         | 0.1287 |
  | 176.0927      | 6.72  | 900  | 43.9972         | 0.1251 |
  | 175.7854      | 7.46  | 1000 | 43.3336         | 0.1253 |
  | 170.2058      | 8.21  | 1100 | 44.0316         | 0.1285 |
  | 157.8171      | 8.96  | 1200 | 42.9391         | 0.1246 |
  | 158.1243      | 9.7   | 1300 | 41.9089         | 0.1216 |
  | 160.1174      | 10.45 | 1400 | 41.7764         | 0.1212 |
  | 157.8857      | 11.19 | 1500 | 41.7168         | 0.1199 |
  | 155.323       | 11.94 | 1600 | 41.5339         | 0.1205 |
  | 149.4838      | 12.69 | 1700 | 41.1427         | 0.1189 |
  | 148.4661      | 13.43 | 1800 | 41.1901         | 0.1181 |
  | 147.2941      | 14.18 | 1900 | 41.1430         | 0.1184 |
  | 151.4415      | 14.93 | 2000 | 41.1998         | 0.1188 |
  | 142.9946      | 15.67 | 2100 | 41.3427         | 0.1180 |
  | 143.8573      | 16.42 | 2200 | 40.9182         | 0.1167 |
  | 144.2671      | 17.16 | 2300 | 41.0134         | 0.1158 |
  | 145.2445      | 17.91 | 2400 | 40.8738         | 0.1170 |
  | 148.3202      | 18.66 | 2500 | 40.6994         | 0.1166 |
  | 138.238       | 19.4  | 2600 | 40.9133         | 0.1173 |
  | 139.9513      | 20.15 | 2700 | 40.8462         | 0.1165 |
  | 142.0799      | 20.9  | 2800 | 40.9641         | 0.1155 |
  | 136.6577      | 21.64 | 2900 | 40.9828         | 0.1162 |
  | 143.027       | 22.39 | 3000 | 41.1197         | 0.1152 |
  | 138.5346      | 23.13 | 3100 | 41.0499         | 0.1153 |
  | 132.8113      | 23.88 | 3200 | 41.1406         | 0.1155 |
  | 136.3161      | 24.63 | 3300 | 41.0155         | 0.1147 |
  | 138.4135      | 25.37 | 3400 | 40.8724         | 0.1147 |
  | 132.4531      | 26.12 | 3500 | 40.8390         | 0.1143 |
  | 131.0835      | 26.87 | 3600 | 41.0005         | 0.1143 |
  | 132.015       | 27.61 | 3700 | 40.9447         | 0.1142 |
  | 132.5831      | 28.36 | 3800 | 40.9810         | 0.1142 |
  | 134.858       | 29.1  | 3900 | 40.9652         | 0.1140 |
  | 135.4016      | 29.85 | 4000 | 40.9574         | 0.1140 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.11.0
  