readme: ---
  license: cc-by-sa-4.0
  tags:
  - generated_from_trainer
  datasets:
  - te_dx_jp
  model-index:
  - name: t5-base-TEDxJP-1front-1body-1rear
    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-1front-1body-1rear
  
  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: 0.4600
  - Wer: 0.1742
  - Mer: 0.1683
  - Wil: 0.2562
  - Wip: 0.7438
  - Hits: 55625
  - Substitutions: 6495
  - Deletions: 2467
  - Insertions: 2291
  - Cer: 0.1364
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
  | 0.6478        | 1.0   | 1457  | 0.4880          | 0.2256 | 0.2100 | 0.2999 | 0.7001 | 54825 | 6842          | 2920      | 4808       | 0.2019 |
  | 0.542         | 2.0   | 2914  | 0.4461          | 0.1886 | 0.1807 | 0.2697 | 0.7303 | 55225 | 6615          | 2747      | 2817       | 0.1577 |
  | 0.4873        | 3.0   | 4371  | 0.4390          | 0.1764 | 0.1702 | 0.2584 | 0.7416 | 55541 | 6519          | 2527      | 2344       | 0.1392 |
  | 0.4271        | 4.0   | 5828  | 0.4361          | 0.1750 | 0.1691 | 0.2567 | 0.7433 | 55512 | 6453          | 2622      | 2226       | 0.1381 |
  | 0.3705        | 5.0   | 7285  | 0.4366          | 0.1741 | 0.1684 | 0.2558 | 0.7442 | 55508 | 6427          | 2652      | 2164       | 0.1358 |
  | 0.3557        | 6.0   | 8742  | 0.4424          | 0.1738 | 0.1679 | 0.2555 | 0.7445 | 55600 | 6453          | 2534      | 2235       | 0.1369 |
  | 0.3838        | 7.0   | 10199 | 0.4471          | 0.1741 | 0.1684 | 0.2562 | 0.7438 | 55550 | 6473          | 2564      | 2210       | 0.1362 |
  | 0.3095        | 8.0   | 11656 | 0.4517          | 0.1746 | 0.1685 | 0.2566 | 0.7434 | 55618 | 6499          | 2470      | 2305       | 0.1367 |
  | 0.306         | 9.0   | 13113 | 0.4573          | 0.1748 | 0.1688 | 0.2570 | 0.7430 | 55601 | 6517          | 2469      | 2304       | 0.1369 |
  | 0.3073        | 10.0  | 14570 | 0.4600          | 0.1742 | 0.1683 | 0.2562 | 0.7438 | 55625 | 6495          | 2467      | 2291       | 0.1364 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu116
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  