readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: ''
    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. -->
  
  # 
  
  This model was trained from scratch on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2965
  - Wer: 0.3144
  
  ## 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: 0.0001
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 8
  - 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: 1000
  - num_epochs: 20.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 2.888         | 0.51  | 400   | 3.7320          | 0.9440 |
  | 3.1636        | 1.02  | 800   | 2.9188          | 1.1916 |
  | 2.773         | 1.53  | 1200  | 2.3347          | 1.0134 |
  | 0.7198        | 2.04  | 1600  | 0.6678          | 0.4826 |
  | 0.5255        | 2.55  | 2000  | 0.4605          | 0.4135 |
  | 0.3961        | 3.06  | 2400  | 0.4266          | 0.3955 |
  | 0.3424        | 3.57  | 2800  | 0.3786          | 0.3741 |
  | 0.3858        | 4.08  | 3200  | 0.3161          | 0.3552 |
  | 0.3218        | 4.59  | 3600  | 0.3029          | 0.3510 |
  | 0.199         | 5.1   | 4000  | 0.2988          | 0.3418 |
  | 0.2054        | 5.61  | 4400  | 0.2873          | 0.3434 |
  | 0.1704        | 6.12  | 4800  | 0.3129          | 0.3432 |
  | 0.1805        | 6.63  | 5200  | 0.2963          | 0.3413 |
  | 0.2091        | 7.14  | 5600  | 0.2755          | 0.3329 |
  | 0.1971        | 7.65  | 6000  | 0.2706          | 0.3309 |
  | 0.1237        | 8.16  | 6400  | 0.2823          | 0.3270 |
  | 0.123         | 8.67  | 6800  | 0.2754          | 0.3246 |
  | 0.103         | 9.18  | 7200  | 0.2917          | 0.3272 |
  | 0.1143        | 9.69  | 7600  | 0.2885          | 0.3305 |
  | 0.156         | 10.2  | 8000  | 0.2810          | 0.3288 |
  | 0.167         | 10.71 | 8400  | 0.2689          | 0.3232 |
  | 0.0815        | 11.22 | 8800  | 0.2899          | 0.3236 |
  | 0.0844        | 11.73 | 9200  | 0.2798          | 0.3225 |
  | 0.0775        | 12.24 | 9600  | 0.2894          | 0.3224 |
  | 0.0677        | 12.75 | 10000 | 0.2838          | 0.3204 |
  | 0.1383        | 13.27 | 10400 | 0.2959          | 0.3211 |
  | 0.1233        | 13.77 | 10800 | 0.2922          | 0.3213 |
  | 0.0688        | 14.29 | 11200 | 0.2903          | 0.3209 |
  | 0.0655        | 14.8  | 11600 | 0.2868          | 0.3182 |
  | 0.0449        | 15.31 | 12000 | 0.2959          | 0.3172 |
  | 0.0421        | 15.82 | 12400 | 0.2966          | 0.3180 |
  | 0.0858        | 16.33 | 12800 | 0.2941          | 0.3164 |
  | 0.0859        | 16.84 | 13200 | 0.2980          | 0.3165 |
  | 0.0561        | 17.35 | 13600 | 0.2965          | 0.3165 |
  | 0.0506        | 17.86 | 14000 | 0.2935          | 0.3148 |
  | 0.0312        | 18.37 | 14400 | 0.2964          | 0.3154 |
  | 0.0403        | 18.88 | 14800 | 0.2967          | 0.3160 |
  | 0.0924        | 19.39 | 15200 | 0.2955          | 0.3147 |
  | 0.0585        | 19.9  | 15600 | 0.2965          | 0.3144 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.0+cu113
  - Datasets 1.18.1
  - Tokenizers 0.11.0
  