readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: retrain_epoch2to5
    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. -->
  
  # retrain_epoch2to5
  
  This model is a fine-tuned version of [alexziweiwang/retrain_first1epoch](https://huggingface.co/alexziweiwang/retrain_first1epoch) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.3244
  - Acc: 0.24
  - Wer: 1.0
  - Correct: 48
  - 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    | 7.8494          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 7.6032        | 0.04  | 10   | 7.4834          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 7.6032        | 0.06  | 15   | 7.1350          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 7.3336        | 0.08  | 20   | 6.8284          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 7.3336        | 0.11  | 25   | 6.5577          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 6.2911        | 0.13  | 30   | 6.3124          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 6.2911        | 0.15  | 35   | 6.0850          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 5.9181        | 0.17  | 40   | 5.8888          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 5.9181        | 0.19  | 45   | 5.6815          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 5.7954        | 0.21  | 50   | 5.4834          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 5.7954        | 0.23  | 55   | 5.3099          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 5.4801        | 0.25  | 60   | 5.1678          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 5.4801        | 0.27  | 65   | 5.0223          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 5.3377        | 0.3   | 70   | 4.8893          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 5.3377        | 0.32  | 75   | 4.7743          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 5.2511        | 0.34  | 80   | 4.6494          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 5.2511        | 0.36  | 85   | 4.5307          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.727         | 0.38  | 90   | 4.4237          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.727         | 0.4   | 95   | 4.3263          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.7653        | 0.42  | 100  | 4.2439          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.7653        | 0.44  | 105  | 4.1589          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.4971        | 0.46  | 110  | 4.0847          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.4971        | 0.48  | 115  | 4.0118          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.0077        | 0.51  | 120  | 3.9382          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.0077        | 0.53  | 125  | 3.8663          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.1693        | 0.55  | 130  | 3.8106          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.1693        | 0.57  | 135  | 3.7580          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.0854        | 0.59  | 140  | 3.7123          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.0854        | 0.61  | 145  | 3.6720          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.1988        | 0.63  | 150  | 3.6260          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 4.1988        | 0.65  | 155  | 3.5853          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 3.9975        | 0.67  | 160  | 3.5463          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 3.9975        | 0.7   | 165  | 3.5122          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 3.6042        | 0.72  | 170  | 3.4862          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 3.6042        | 0.74  | 175  | 3.4631          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 3.7347        | 0.76  | 180  | 3.4406          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 3.7347        | 0.78  | 185  | 3.4202          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 3.8336        | 0.8   | 190  | 3.4014          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 3.8336        | 0.82  | 195  | 3.3855          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 3.7454        | 0.84  | 200  | 3.3703          | 0.24 | 1.0 | 48      | 200   | 200    |
  | 3.7454        | 0.86  | 205  | 3.3576       