readme: ---
  license: cc-by-sa-4.0
  tags:
  - generated_from_trainer
  datasets:
  - te_dx_jp
  model-index:
  - name: t5-base-TEDxJP-10front-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-10front-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: 0.4586
  - Wer: 0.1729
  - Mer: 0.1671
  - Wil: 0.2545
  - Wip: 0.7455
  - Hits: 55669
  - Substitutions: 6448
  - Deletions: 2470
  - Insertions: 2249
  - Cer: 0.1350
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
  | 0.6477        | 1.0   | 1457  | 0.4829          | 0.2234 | 0.2082 | 0.2973 | 0.7027 | 54891 | 6766          | 2930      | 4734       | 0.2060 |
  | 0.5306        | 2.0   | 2914  | 0.4366          | 0.1808 | 0.1743 | 0.2615 | 0.7385 | 55312 | 6431          | 2844      | 2402       | 0.1439 |
  | 0.4743        | 3.0   | 4371  | 0.4311          | 0.1827 | 0.1752 | 0.2623 | 0.7377 | 55558 | 6456          | 2573      | 2771       | 0.1483 |
  | 0.4299        | 4.0   | 5828  | 0.4286          | 0.1778 | 0.1711 | 0.2580 | 0.7420 | 55641 | 6422          | 2524      | 2540       | 0.1419 |
  | 0.3815        | 5.0   | 7285  | 0.4321          | 0.1741 | 0.1680 | 0.2554 | 0.7446 | 55673 | 6448          | 2466      | 2330       | 0.1379 |
  | 0.3508        | 6.0   | 8742  | 0.4392          | 0.1737 | 0.1677 | 0.2547 | 0.7453 | 55683 | 6417          | 2487      | 2312       | 0.1373 |
  | 0.3594        | 7.0   | 10199 | 0.4477          | 0.1726 | 0.1666 | 0.2528 | 0.7472 | 55757 | 6344          | 2486      | 2319       | 0.1349 |
  | 0.2975        | 8.0   | 11656 | 0.4509          | 0.1726 | 0.1668 | 0.2537 | 0.7463 | 55691 | 6401          | 2495      | 2251       | 0.1349 |
  | 0.2947        | 9.0   | 13113 | 0.4550          | 0.1725 | 0.1667 | 0.2539 | 0.7461 | 55700 | 6426          | 2461      | 2257       | 0.1347 |
  | 0.2892        | 10.0  | 14570 | 0.4586          | 0.1729 | 0.1671 | 0.2545 | 0.7455 | 55669 | 6448          | 2470      | 2249       | 0.1350 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu116
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  