readme: ---
  license: cc-by-sa-4.0
  tags:
  - generated_from_trainer
  datasets:
  - te_dx_jp
  model-index:
  - name: t5-base-TEDxJP-2front-1body-0rear
    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-2front-1body-0rear
  
  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: 0.4717
  - Wer: 0.1762
  - Mer: 0.1701
  - Wil: 0.2575
  - Wip: 0.7425
  - Hits: 55549
  - Substitutions: 6453
  - Deletions: 2585
  - Insertions: 2345
  - Cer: 0.1398
  
  ## 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: 32
  - eval_batch_size: 32
  - 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
  | 0.6666        | 1.0   | 1457  | 0.5030          | 0.2075 | 0.1970 | 0.2883 | 0.7117 | 54622 | 6855          | 3110      | 3434       | 0.1720 |
  | 0.567         | 2.0   | 2914  | 0.4611          | 0.1950 | 0.1859 | 0.2750 | 0.7250 | 55142 | 6648          | 2797      | 3148       | 0.1598 |
  | 0.5029        | 3.0   | 4371  | 0.4463          | 0.1832 | 0.1762 | 0.2640 | 0.7360 | 55317 | 6492          | 2778      | 2564       | 0.1445 |
  | 0.443         | 4.0   | 5828  | 0.4452          | 0.1791 | 0.1728 | 0.2606 | 0.7394 | 55375 | 6482          | 2730      | 2354       | 0.1408 |
  | 0.3979        | 5.0   | 7285  | 0.4473          | 0.1782 | 0.1719 | 0.2592 | 0.7408 | 55434 | 6438          | 2715      | 2355       | 0.1400 |
  | 0.3745        | 6.0   | 8742  | 0.4521          | 0.1757 | 0.1698 | 0.2573 | 0.7427 | 55501 | 6450          | 2636      | 2264       | 0.1373 |
  | 0.3889        | 7.0   | 10199 | 0.4572          | 0.1775 | 0.1713 | 0.2586 | 0.7414 | 55458 | 6438          | 2691      | 2334       | 0.1398 |
  | 0.3247        | 8.0   | 11656 | 0.4650          | 0.1752 | 0.1693 | 0.2564 | 0.7436 | 55516 | 6409          | 2662      | 2245       | 0.1372 |
  | 0.3207        | 9.0   | 13113 | 0.4693          | 0.1766 | 0.1703 | 0.2580 | 0.7420 | 55549 | 6474          | 2564      | 2367       | 0.1400 |
  | 0.3264        | 10.0  | 14570 | 0.4717          | 0.1762 | 0.1701 | 0.2575 | 0.7425 | 55549 | 6453          | 2585      | 2345       | 0.1398 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu116
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  