readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: med_v1_M01
    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. -->
  
  # med_v1_M01
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Cer: 0.8926
  - Loss: 3.2885
  - Wer: 1.0
  
  ## 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: 20
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 13500
  - num_epochs: 2000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step   | Cer    | Validation Loss | Wer |
  |:-------------:|:------:|:------:|:------:|:---------------:|:---:|
  | 16.9472       | 200.0  | 27000  | 0.9041 | 3.2161          | 1.0 |
  | 2.6444        | 400.0  | 54000  | 0.8959 | 3.2246          | 1.0 |
  | 2.5434        | 600.0  | 81000  | 0.8942 | 3.2352          | 1.0 |
  | 2.4925        | 800.0  | 108000 | 0.8959 | 3.2468          | 1.0 |
  | 2.4631        | 1000.0 | 135000 | 0.8942 | 3.2656          | 1.0 |
  | 2.4434        | 1200.0 | 162000 | 0.8942 | 3.2616          | 1.0 |
  | 2.4292        | 1400.0 | 189000 | 0.8942 | 3.2840          | 1.0 |
  | 2.4203        | 1600.0 | 216000 | 0.8926 | 3.2791          | 1.0 |
  | 2.4148        | 1800.0 | 243000 | 0.8926 | 3.2866          | 1.0 |
  | 2.4112        | 2000.0 | 270000 | 0.8926 | 3.2885          | 1.0 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.2+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  