readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: retrain5_oneTimeTraining_MTL-1epoch
    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. -->
  
  # retrain5_oneTimeTraining_MTL-1epoch
  
  This model is a fine-tuned version of [alexziweiwang/exp21-uaspeech-foundation](https://huggingface.co/alexziweiwang/exp21-uaspeech-foundation) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 7.1861
  - Acc: 0.285
  - Wer: 1.1126
  - Correct: 57
  - Total: 200
  - Strlen: 200
  
  ## 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: 9e-06
  - train_batch_size: 2
  - eval_batch_size: 1
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 8
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Acc   | Wer    | Correct | Total | Strlen |
  |:-------------:|:-----:|:----:|:---------------:|:-----:|:------:|:-------:|:-----:|:------:|
  | No log        | 0.02  | 5    | 13.9337         | 0.01  | 1.2925 | 2       | 200   | 200    |
  | 12.4373       | 0.04  | 10   | 13.7513         | 0.08  | 1.5296 | 16      | 200   | 200    |
  | 12.4373       | 0.06  | 15   | 13.5517         | 0.125 | 2.1126 | 25      | 200   | 200    |
  | 12.6667       | 0.08  | 20   | 13.3400         | 0.165 | 2.5791 | 33      | 200   | 200    |
  | 12.6667       | 0.11  | 25   | 13.1141         | 0.205 | 3.6561 | 41      | 200   | 200    |
  | 11.1856       | 0.13  | 30   | 12.8805         | 0.22  | 2.7451 | 44      | 200   | 200    |
  | 11.1856       | 0.15  | 35   | 12.6423         | 0.245 | 2.5178 | 49      | 200   | 200    |
  | 10.6635       | 0.17  | 40   | 12.4028         | 0.27  | 2.4308 | 54      | 200   | 200    |
  | 10.6635       | 0.19  | 45   | 12.1660         | 0.3   | 2.1818 | 60      | 200   | 200    |
  | 10.7952       | 0.21  | 50   | 11.9291         | 0.305 | 1.9348 | 61      | 200   | 200    |
  | 10.7952       | 0.23  | 55   | 11.6945         | 0.31  | 1.6858 | 62      | 200   | 200    |
  | 10.3867       | 0.25  | 60   | 11.4608         | 0.315 | 1.5237 | 63      | 200   | 200    |
  | 10.3867       | 0.27  | 65   | 11.2313         | 0.315 | 1.3953 | 63      | 200   | 200    |
  | 10.252        | 0.3   | 70   | 11.0102         | 0.315 | 1.3162 | 63      | 200   | 200    |
  | 10.252        | 0.32  | 75   | 10.7918         | 0.315 | 1.2826 | 63      | 200   | 200    |
  | 10.1788       | 0.34  | 80   | 10.5736         | 0.315 | 1.2628 | 63      | 200   | 200    |
  | 10.1788       | 0.36  | 85   | 10.3607         | 0.32  | 1.2391 | 64      | 200   | 200    |
  | 9.1361        | 0.38  | 90   | 10.1527         | 0.31  | 1.2253 | 62      | 200   | 200    |
  | 9.1361        | 0.4   | 95   | 9.9507          | 0.31  | 1.2036 | 62      | 200   | 200    |
  | 9.5447        | 0.42  | 100  | 9.7553          | 0.315 | 1.2095 | 63      | 200   | 200    |
  | 9.5447        | 0.44  | 105  | 9.5599          | 0.31  | 1.2016 | 62      | 200   | 200    |
  | 9.1579        | 0.46  | 110  | 9.3711          | 0.295 | 1.1996 | 59      | 200   | 200    |
  | 9.1579        | 0.48  | 115  | 9.1892          | 0.295 | 1.1897 | 59      | 200   | 200    |
  | 7.9217        | 0.51  | 120  | 9.0143          | 0.3   | 1.1858 | 60      | 200   | 200    |
  | 7.9217        | 0.53  | 125  | 8.8493          | 0.305 | 1.1719 | 61      | 200   | 200    |
  | 8.4439        | 0.55  | 130  | 8.6946          | 0.305 | 1.1739 | 61      | 200   | 200    |
  | 8.4439        | 0.57  | 135  | 8.5492          | 0.31  | 1.1581 | 62      | 200   | 200    |
  | 8.0639        | 0.59  | 140  | 8.4153          | 0.315 | 1.1502 | 63      | 200   | 200    |
  | 8.0639        | 0.61  | 145  | 8.2872          | 0.32  | 1.1482 | 64      | 200   | 200    |
  | 8.4173        | 0.63  | 150  | 8.1649          | 0.33  | 1.1443 | 66      | 200   | 200    |
  | 8.4173        | 0.65  | 155  | 8.0500          | 0.325 | 1.1403 | 65      | 200   | 200    |
  | 7.8991        | 0.67  | 160  | 7.9422          | 0.33  | 1.1364 | 66      | 200   | 200    |
  | 7.8991        | 0.7   | 165  | 7.8410          | 0.32  | 1.1344 | 64      | 200   | 200    |
  | 6.9206        | 0.72  | 170  | 7.7469          | 0.32  | 1.1304 | 64      | 200   | 200    |
  | 6.9206        | 0.74  | 175  | 7.6601          | 0.325 | 1.1285 | 65      | 200   | 200    |
  | 7.1911        | 0.76  | 180  | 7.5832          | 0.305 | 1.1206 | 61      | 200   | 200    |
  | 7.1911        | 0.78  | 185  | 7.5163          | 0.305 | 1.1225 | 61      | 200   | 200    |
  | 7.201         | 0.8   | 190  | 7.4565          | 0.305 | 1.1245 | 61      | 200   | 200    |
  | 7.201         