---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-5front-1body-5rear
  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-5front-1body-5rear

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: 0.4411
- Wer: 0.1694
- Mer: 0.1636
- Wil: 0.2489
- Wip: 0.7511
- Hits: 55916
- Substitutions: 6268
- Deletions: 2403
- Insertions: 2267
- Cer: 0.1371

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.5975        | 1.0   | 1457  | 0.4673          | 0.2058 | 0.1947 | 0.2831 | 0.7169 | 54961 | 6617          | 3009      | 3665       | 0.1746 |
| 0.5623        | 2.0   | 2914  | 0.4246          | 0.1801 | 0.1737 | 0.2603 | 0.7397 | 55335 | 6381          | 2871      | 2378       | 0.1452 |
| 0.4438        | 3.0   | 4371  | 0.4104          | 0.1735 | 0.1675 | 0.2541 | 0.7459 | 55705 | 6379          | 2503      | 2326       | 0.1357 |
| 0.4177        | 4.0   | 5828  | 0.4119          | 0.1704 | 0.1647 | 0.2504 | 0.7496 | 55837 | 6299          | 2451      | 2258       | 0.1338 |
| 0.3548        | 5.0   | 7285  | 0.4171          | 0.1690 | 0.1637 | 0.2487 | 0.7513 | 55785 | 6228          | 2574      | 2115       | 0.1328 |
| 0.3115        | 6.0   | 8742  | 0.4245          | 0.1687 | 0.1633 | 0.2484 | 0.7516 | 55838 | 6243          | 2506      | 2148       | 0.1340 |
| 0.2997        | 7.0   | 10199 | 0.4302          | 0.1706 | 0.1647 | 0.2503 | 0.7497 | 55898 | 6300          | 2389      | 2329       | 0.1351 |
| 0.2977        | 8.0   | 11656 | 0.4361          | 0.1699 | 0.1642 | 0.2496 | 0.7504 | 55879 | 6278          | 2430      | 2266       | 0.1342 |
| 0.2639        | 9.0   | 13113 | 0.4393          | 0.1688 | 0.1632 | 0.2486 | 0.7514 | 55891 | 6265          | 2431      | 2208       | 0.1365 |
| 0.2879        | 10.0  | 14570 | 0.4411          | 0.1694 | 0.1636 | 0.2489 | 0.7511 | 55916 | 6268          | 2403      | 2267       | 0.1371 |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1