readme: ---
  license: cc-by-sa-4.0
  tags:
  - generated_from_trainer
  datasets:
  - te_dx_jp
  model-index:
  - name: t5-base-TEDxJP-4front-1body-4rear
    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-4front-1body-4rear
  
  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: 0.4406
  - Wer: 0.1708
  - Mer: 0.1650
  - Wil: 0.2510
  - Wip: 0.7490
  - Hits: 55830
  - Substitutions: 6334
  - Deletions: 2423
  - Insertions: 2273
  - Cer: 0.1334
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
  | 0.6266        | 1.0   | 1457  | 0.4764          | 0.2167 | 0.2030 | 0.2919 | 0.7081 | 54977 | 6723          | 2887      | 4389       | 0.1978 |
  | 0.512         | 2.0   | 2914  | 0.4281          | 0.1787 | 0.1727 | 0.2600 | 0.7400 | 55299 | 6432          | 2856      | 2253       | 0.1408 |
  | 0.4636        | 3.0   | 4371  | 0.4205          | 0.1775 | 0.1708 | 0.2582 | 0.7418 | 55665 | 6466          | 2456      | 2540       | 0.1383 |
  | 0.4055        | 4.0   | 5828  | 0.4158          | 0.1721 | 0.1663 | 0.2529 | 0.7471 | 55724 | 6376          | 2487      | 2250       | 0.1344 |
  | 0.356         | 5.0   | 7285  | 0.4195          | 0.1711 | 0.1654 | 0.2520 | 0.7480 | 55769 | 6376          | 2442      | 2235       | 0.1338 |
  | 0.3273        | 6.0   | 8742  | 0.4228          | 0.1700 | 0.1644 | 0.2506 | 0.7494 | 55792 | 6333          | 2462      | 2183       | 0.1330 |
  | 0.3586        | 7.0   | 10199 | 0.4288          | 0.1702 | 0.1645 | 0.2506 | 0.7494 | 55814 | 6331          | 2442      | 2219       | 0.1326 |
  | 0.2836        | 8.0   | 11656 | 0.4339          | 0.1710 | 0.1651 | 0.2515 | 0.7485 | 55833 | 6359          | 2395      | 2290       | 0.1334 |
  | 0.285         | 9.0   | 13113 | 0.4370          | 0.1708 | 0.1649 | 0.2509 | 0.7491 | 55854 | 6330          | 2403      | 2297       | 0.1333 |
  | 0.285         | 10.0  | 14570 | 0.4406          | 0.1708 | 0.1650 | 0.2510 | 0.7490 | 55830 | 6334          | 2423      | 2273       | 0.1334 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu116
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  