readme: ---
  license: cc-by-sa-4.0
  tags:
  - generated_from_trainer
  datasets:
  - te_dx_jp
  model-index:
  - name: t5-base-TEDxJP-3front-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-3front-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: 0.4641
  - Wer: 0.1743
  - Mer: 0.1684
  - Wil: 0.2557
  - Wip: 0.7443
  - Hits: 55594
  - Substitutions: 6428
  - Deletions: 2565
  - Insertions: 2267
  - Cer: 0.1368
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
  | 0.6567        | 1.0   | 1457  | 0.4959          | 0.2072 | 0.1966 | 0.2877 | 0.7123 | 54688 | 6836          | 3063      | 3486       | 0.1936 |
  | 0.5486        | 2.0   | 2914  | 0.4504          | 0.1870 | 0.1796 | 0.2677 | 0.7323 | 55158 | 6518          | 2911      | 2647       | 0.1528 |
  | 0.4957        | 3.0   | 4371  | 0.4410          | 0.1764 | 0.1705 | 0.2578 | 0.7422 | 55412 | 6429          | 2746      | 2216       | 0.1375 |
  | 0.4371        | 4.0   | 5828  | 0.4379          | 0.1761 | 0.1702 | 0.2572 | 0.7428 | 55447 | 6407          | 2733      | 2232       | 0.1377 |
  | 0.387         | 5.0   | 7285  | 0.4408          | 0.1756 | 0.1696 | 0.2562 | 0.7438 | 55510 | 6372          | 2705      | 2263       | 0.1399 |
  | 0.3589        | 6.0   | 8742  | 0.4466          | 0.1737 | 0.1681 | 0.2552 | 0.7448 | 55532 | 6406          | 2649      | 2165       | 0.1359 |
  | 0.3876        | 7.0   | 10199 | 0.4532          | 0.1746 | 0.1689 | 0.2563 | 0.7437 | 55491 | 6436          | 2660      | 2179       | 0.1363 |
  | 0.3199        | 8.0   | 11656 | 0.4591          | 0.1738 | 0.1681 | 0.2554 | 0.7446 | 55568 | 6431          | 2588      | 2208       | 0.1362 |
  | 0.3079        | 9.0   | 13113 | 0.4625          | 0.1743 | 0.1685 | 0.2557 | 0.7443 | 55579 | 6425          | 2583      | 2252       | 0.1366 |
  | 0.3124        | 10.0  | 14570 | 0.4641          | 0.1743 | 0.1684 | 0.2557 | 0.7443 | 55594 | 6428          | 2565      | 2267       | 0.1368 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu116
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  