readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: retrain2_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. -->
  
  # retrain2_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: 5.9312
  - Acc: 0.265
  - Wer: 1.0
  - Correct: 53
  - 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    | 13.6638         | 0.005 | 1.6126 | 1       | 200   | 200    |
  | 12.2282       | 0.04  | 10   | 13.4030         | 0.005 | 1.4743 | 1       | 200   | 200    |
  | 12.2282       | 0.06  | 15   | 13.1289         | 0.005 | 1.3953 | 1       | 200   | 200    |
  | 12.3565       | 0.08  | 20   | 12.8538         | 0.005 | 1.3043 | 1       | 200   | 200    |
  | 12.3565       | 0.11  | 25   | 12.5711         | 0.005 | 1.2095 | 1       | 200   | 200    |
  | 10.7997       | 0.13  | 30   | 12.2891         | 0.005 | 1.1462 | 1       | 200   | 200    |
  | 10.7997       | 0.15  | 35   | 12.0060         | 0.005 | 1.0909 | 1       | 200   | 200    |
  | 10.1556       | 0.17  | 40   | 11.7183         | 0.005 | 1.0632 | 1       | 200   | 200    |
  | 10.1556       | 0.19  | 45   | 11.4347         | 0.01  | 1.0395 | 2       | 200   | 200    |
  | 10.3187       | 0.21  | 50   | 11.1549         | 0.01  | 1.0178 | 2       | 200   | 200    |
  | 10.3187       | 0.23  | 55   | 10.8828         | 0.01  | 1.0099 | 2       | 200   | 200    |
  | 9.8042        | 0.25  | 60   | 10.6161         | 0.01  | 1.0040 | 2       | 200   | 200    |
  | 9.8042        | 0.27  | 65   | 10.3539         | 0.01  | 0.9980 | 2       | 200   | 200    |
  | 9.6489        | 0.3   | 70   | 10.0954         | 0.015 | 1.0    | 3       | 200   | 200    |
  | 9.6489        | 0.32  | 75   | 9.8456          | 0.025 | 1.0    | 5       | 200   | 200    |
  | 9.6112        | 0.34  | 80   | 9.5980          | 0.045 | 1.0    | 9       | 200   | 200    |
  | 9.6112        | 0.36  | 85   | 9.3535          | 0.055 | 1.0    | 11      | 200   | 200    |
  | 8.4257        | 0.38  | 90   | 9.1168          | 0.085 | 1.0    | 17      | 200   | 200    |
  | 8.4257        | 0.4   | 95   | 8.8920          | 0.105 | 1.0    | 21      | 200   | 200    |
  | 8.7311        | 0.42  | 100  | 8.6739          | 0.11  | 1.0    | 22      | 200   | 200    |
  | 8.7311        | 0.44  | 105  | 8.4607          | 0.135 | 1.0    | 27      | 200   | 200    |
  | 8.3653        | 0.46  | 110  | 8.2551          | 0.165 | 1.0    | 33      | 200   | 200    |
  | 8.3653        | 0.48  | 115  | 8.0573          | 0.17  | 1.0    | 34      | 200   | 200    |
  | 7.1342        | 0.51  | 120  | 7.8700          | 0.175 | 1.0    | 35      | 200   | 200    |
  | 7.1342        | 0.53  | 125  | 7.6908          | 0.185 | 1.0    | 37      | 200   | 200    |
  | 7.5411        | 0.55  | 130  | 7.5221          | 0.205 | 1.0    | 41      | 200   | 200    |
  | 7.5411        | 0.57  | 135  | 7.3628          | 0.22  | 1.0    | 44      | 200   | 200    |
  | 7.2449        | 0.59  | 140  | 7.2131          | 0.23  | 1.0    | 46      | 200   | 200    |
  | 7.2449        | 0.61  | 145  | 7.0735          | 0.23  | 1.0    | 46      | 200   | 200    |
  | 7.5166        | 0.63  | 150  | 6.9396          | 0.25  | 1.0    | 50      | 200   | 200    |
  | 7.5166        | 0.65  | 155  | 6.8186          | 0.25  | 1.0    | 50      | 200   | 200    |
  | 7.0016        | 0.67  | 160  | 6.7015          | 0.25  | 1.0    | 50      | 200   | 200    |
  | 7.0016        | 0.7   | 165  | 6.5904          | 0.25  | 1.0    | 50      | 200   | 200    |
  | 6.0715        | 0.72  | 170  | 6.4879          | 0.255 | 1.0    | 51      | 200   | 200    |
  | 6.0715        | 0.74  | 175  | 6.3980          | 0.26  | 1.0    | 52      | 200   | 200    |
  | 6.312         | 0.76  | 180  | 6.3198          | 0.26  | 1.0    | 52      | 200   | 200    |
  | 6.312         | 0.78  | 185  | 6.2532          | 0.26  | 1.0    | 52      | 200   | 200    |
  | 6.3694        | 0.8   | 190  | 6.1952          | 0.26  | 1.0    | 52      | 200   | 200    |
  | 6.3694        | 0