readme: ---
  license: cc-by-sa-4.0
  tags:
  - generated_from_trainer
  datasets:
  - te_dx_jp
  model-index:
  - name: t5-base-TEDxJP-1body-1context
    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. -->
  
  # t5-base-TEDxJP-1body-1context
  
  This model is a fine-tuned version of [sonoisa/t5-base-japanese](https://huggingface.co/sonoisa/t5-base-japanese) on the te_dx_jp dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5061
  - Wer: 0.1990
  - Mer: 0.1913
  - Wil: 0.2823
  - Wip: 0.7177
  - Hits: 55830
  - Substitutions: 6943
  - Deletions: 3598
  - Insertions: 2664
  - Cer: 0.1763
  
  ## 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: 64
  - 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_ratio: 0.1
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    | Mer    | Wil    | Wip    | Hits  | Substitutions | Deletions | Insertions | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
  | 0.7277        | 1.0   | 746  | 0.5799          | 0.2384 | 0.2256 | 0.3188 | 0.6812 | 54323 | 7170          | 4878      | 3777       | 0.2371 |
  | 0.6278        | 2.0   | 1492 | 0.5254          | 0.2070 | 0.1997 | 0.2905 | 0.7095 | 55045 | 6885          | 4441      | 2412       | 0.1962 |
  | 0.5411        | 3.0   | 2238 | 0.5076          | 0.2022 | 0.1950 | 0.2858 | 0.7142 | 55413 | 6902          | 4056      | 2463       | 0.1805 |
  | 0.53          | 4.0   | 2984 | 0.5020          | 0.1979 | 0.1911 | 0.2814 | 0.7186 | 55599 | 6849          | 3923      | 2362       | 0.1761 |
  | 0.5094        | 5.0   | 3730 | 0.4999          | 0.1987 | 0.1915 | 0.2828 | 0.7172 | 55651 | 6944          | 3776      | 2465       | 0.1742 |
  | 0.4783        | 6.0   | 4476 | 0.5016          | 0.1985 | 0.1914 | 0.2826 | 0.7174 | 55684 | 6947          | 3740      | 2490       | 0.1753 |
  | 0.4479        | 7.0   | 5222 | 0.5035          | 0.1976 | 0.1905 | 0.2819 | 0.7181 | 55726 | 6961          | 3684      | 2468       | 0.1733 |
  | 0.4539        | 8.0   | 5968 | 0.5022          | 0.1967 | 0.1896 | 0.2807 | 0.7193 | 55795 | 6938          | 3638      | 2477       | 0.1729 |
  | 0.4632        | 9.0   | 6714 | 0.5034          | 0.1991 | 0.1913 | 0.2824 | 0.7176 | 55844 | 6942          | 3585      | 2687       | 0.1758 |
  | 0.4201        | 10.0  | 7460 | 0.5061          | 0.1990 | 0.1913 | 0.2823 | 0.7177 | 55830 | 6943          | 3598      | 2664       | 0.1763 |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.10.0+cu102
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  