readme: ---
  license: cc-by-sa-4.0
  tags:
  - generated_from_trainer
  datasets:
  - te_dx_jp
  model-index:
  - name: t5-base-TEDxJP-6front-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-6front-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: 0.4613
  - Wer: 0.1753
  - Mer: 0.1692
  - Wil: 0.2565
  - Wip: 0.7435
  - Hits: 55602
  - Substitutions: 6443
  - Deletions: 2542
  - Insertions: 2338
  - Cer: 0.1381
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
  | 0.6523        | 1.0   | 1457  | 0.4912          | 0.2014 | 0.1921 | 0.2829 | 0.7171 | 54699 | 6782          | 3106      | 3118       | 0.1699 |
  | 0.5429        | 2.0   | 2914  | 0.4424          | 0.1879 | 0.1801 | 0.2682 | 0.7318 | 55234 | 6529          | 2824      | 2782       | 0.1505 |
  | 0.4888        | 3.0   | 4371  | 0.4371          | 0.1761 | 0.1699 | 0.2567 | 0.7433 | 55564 | 6391          | 2632      | 2353       | 0.1376 |
  | 0.4287        | 4.0   | 5828  | 0.4328          | 0.1738 | 0.1680 | 0.2542 | 0.7458 | 55584 | 6332          | 2671      | 2223       | 0.1350 |
  | 0.387         | 5.0   | 7285  | 0.4357          | 0.1747 | 0.1687 | 0.2555 | 0.7445 | 55627 | 6399          | 2561      | 2326       | 0.1360 |
  | 0.3497        | 6.0   | 8742  | 0.4405          | 0.1750 | 0.1690 | 0.2558 | 0.7442 | 55587 | 6399          | 2601      | 2301       | 0.1370 |
  | 0.3703        | 7.0   | 10199 | 0.4480          | 0.1748 | 0.1689 | 0.2560 | 0.7440 | 55554 | 6416          | 2617      | 2258       | 0.1363 |
  | 0.3038        | 8.0   | 11656 | 0.4542          | 0.1746 | 0.1686 | 0.2554 | 0.7446 | 55638 | 6399          | 2550      | 2331       | 0.1369 |
  | 0.3045        | 9.0   | 13113 | 0.4574          | 0.1752 | 0.1691 | 0.2564 | 0.7436 | 55596 | 6441          | 2550      | 2324       | 0.1381 |
  | 0.3008        | 10.0  | 14570 | 0.4613          | 0.1753 | 0.1692 | 0.2565 | 0.7435 | 55602 | 6443          | 2542      | 2338       | 0.1381 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu116
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  