readme: ---
  license: cc-by-sa-4.0
  tags:
  - generated_from_trainer
  datasets:
  - te_dx_jp
  model-index:
  - name: t5-base-TEDxJP-7front-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-7front-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: 0.4563
  - Wer: 0.1763
  - Mer: 0.1699
  - Wil: 0.2573
  - Wip: 0.7427
  - Hits: 55638
  - Substitutions: 6453
  - Deletions: 2496
  - Insertions: 2439
  - Cer: 0.1383
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
  | 0.6569        | 1.0   | 1457  | 0.4908          | 0.2308 | 0.2137 | 0.3042 | 0.6958 | 54844 | 6924          | 2819      | 5165       | 0.2114 |
  | 0.5393        | 2.0   | 2914  | 0.4417          | 0.1916 | 0.1830 | 0.2706 | 0.7294 | 55263 | 6515          | 2809      | 3053       | 0.1559 |
  | 0.4959        | 3.0   | 4371  | 0.4334          | 0.1776 | 0.1709 | 0.2574 | 0.7426 | 55660 | 6391          | 2536      | 2543       | 0.1398 |
  | 0.4306        | 4.0   | 5828  | 0.4302          | 0.1755 | 0.1693 | 0.2563 | 0.7437 | 55618 | 6414          | 2555      | 2367       | 0.1372 |
  | 0.3862        | 5.0   | 7285  | 0.4321          | 0.1752 | 0.1690 | 0.2561 | 0.7439 | 55653 | 6430          | 2504      | 2384       | 0.1369 |
  | 0.3423        | 6.0   | 8742  | 0.4376          | 0.1772 | 0.1705 | 0.2576 | 0.7424 | 55660 | 6430          | 2497      | 2517       | 0.1384 |
  | 0.3705        | 7.0   | 10199 | 0.4438          | 0.1746 | 0.1686 | 0.2559 | 0.7441 | 55589 | 6431          | 2567      | 2277       | 0.1358 |
  | 0.2991        | 8.0   | 11656 | 0.4484          | 0.1763 | 0.1698 | 0.2571 | 0.7429 | 55650 | 6444          | 2493      | 2448       | 0.1382 |
  | 0.2903        | 9.0   | 13113 | 0.4541          | 0.1764 | 0.1699 | 0.2570 | 0.7430 | 55655 | 6428          | 2504      | 2461       | 0.1384 |
  | 0.2937        | 10.0  | 14570 | 0.4563          | 0.1763 | 0.1699 | 0.2573 | 0.7427 | 55638 | 6453          | 2496      | 2439       | 0.1383 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu116
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  