---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-10front-1body-10rear
  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-10front-1body-10rear

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: 0.4366
- Wer: 0.1686
- Mer: 0.1630
- Wil: 0.2490
- Wip: 0.7510
- Hits: 55913
- Substitutions: 6325
- Deletions: 2349
- Insertions: 2213
- Cer: 0.1324

## 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: 30
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.5904        | 1.0   | 1457  | 0.4553          | 0.2049 | 0.1941 | 0.2824 | 0.7176 | 54935 | 6595          | 3057      | 3580       | 0.1816 |
| 0.5001        | 2.0   | 2914  | 0.4201          | 0.1858 | 0.1776 | 0.2657 | 0.7343 | 55561 | 6554          | 2472      | 2973       | 0.1501 |
| 0.4615        | 3.0   | 4371  | 0.4099          | 0.1748 | 0.1685 | 0.2544 | 0.7456 | 55706 | 6326          | 2555      | 2410       | 0.1414 |
| 0.3988        | 4.0   | 5828  | 0.4040          | 0.1710 | 0.1654 | 0.2514 | 0.7486 | 55734 | 6319          | 2534      | 2189       | 0.1346 |
| 0.3859        | 5.0   | 7285  | 0.4131          | 0.1689 | 0.1635 | 0.2487 | 0.7513 | 55808 | 6245          | 2534      | 2129       | 0.1327 |
| 0.3259        | 6.0   | 8742  | 0.4138          | 0.1695 | 0.1639 | 0.2508 | 0.7492 | 55837 | 6400          | 2350      | 2198       | 0.1325 |
| 0.2915        | 7.0   | 10199 | 0.4233          | 0.1696 | 0.1637 | 0.2499 | 0.7501 | 55932 | 6344          | 2311      | 2297       | 0.1329 |
| 0.2638        | 8.0   | 11656 | 0.4298          | 0.1689 | 0.1633 | 0.2492 | 0.7508 | 55892 | 6319          | 2376      | 2213       | 0.1325 |
| 0.2888        | 9.0   | 13113 | 0.4321          | 0.1686 | 0.1630 | 0.2492 | 0.7508 | 55909 | 6343          | 2335      | 2210       | 0.1319 |
| 0.2614        | 10.0  | 14570 | 0.4366          | 0.1686 | 0.1630 | 0.2490 | 0.7510 | 55913 | 6325          | 2349      | 2213       | 0.1324 |


### Framework versions

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