---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-6front-1body-6rear
  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-6rear

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: 0.4380
- Wer: 0.1700
- Mer: 0.1642
- Wil: 0.2501
- Wip: 0.7499
- Hits: 55894
- Substitutions: 6327
- Deletions: 2366
- Insertions: 2286
- Cer: 0.1345

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.5938        | 1.0   | 1457  | 0.4764          | 0.2123 | 0.1997 | 0.2886 | 0.7114 | 54961 | 6701          | 2925      | 4085       | 0.1721 |
| 0.4817        | 2.0   | 2914  | 0.4166          | 0.1827 | 0.1754 | 0.2615 | 0.7385 | 55462 | 6356          | 2769      | 2676       | 0.1470 |
| 0.4467        | 3.0   | 4371  | 0.4119          | 0.1715 | 0.1660 | 0.2530 | 0.7470 | 55677 | 6410          | 2500      | 2169       | 0.1339 |
| 0.3818        | 4.0   | 5828  | 0.4134          | 0.1714 | 0.1654 | 0.2522 | 0.7478 | 55837 | 6396          | 2354      | 2319       | 0.1340 |
| 0.3577        | 5.0   | 7285  | 0.4171          | 0.1716 | 0.1653 | 0.2509 | 0.7491 | 55938 | 6303          | 2346      | 2432       | 0.1339 |
| 0.3222        | 6.0   | 8742  | 0.4195          | 0.1681 | 0.1628 | 0.2484 | 0.7516 | 55829 | 6282          | 2476      | 2099       | 0.1314 |
| 0.2938        | 7.0   | 10199 | 0.4242          | 0.1685 | 0.1634 | 0.2489 | 0.7511 | 55753 | 6267          | 2567      | 2052       | 0.1327 |
| 0.3174        | 8.0   | 11656 | 0.4269          | 0.1676 | 0.1624 | 0.2482 | 0.7518 | 55846 | 6299          | 2442      | 2083       | 0.1326 |
| 0.277         | 9.0   | 13113 | 0.4332          | 0.1700 | 0.1644 | 0.2505 | 0.7495 | 55831 | 6331          | 2425      | 2227       | 0.1346 |
| 0.2625        | 10.0  | 14570 | 0.4380          | 0.1700 | 0.1642 | 0.2501 | 0.7499 | 55894 | 6327          | 2366      | 2286       | 0.1345 |


### Framework versions

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