---
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: 0.4393
- Wer: 0.1715
- Mer: 0.1657
- Wil: 0.2520
- Wip: 0.7480
- Hits: 55766
- Substitutions: 6346
- Deletions: 2475
- Insertions: 2256
- Cer: 0.1352

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.5978        | 1.0   | 1457  | 0.4748          | 0.2133 | 0.2003 | 0.2897 | 0.7103 | 55011 | 6755          | 2821      | 4200       | 0.1826 |
| 0.4837        | 2.0   | 2914  | 0.4190          | 0.1803 | 0.1737 | 0.2604 | 0.7396 | 55400 | 6393          | 2794      | 2459       | 0.1464 |
| 0.4576        | 3.0   | 4371  | 0.4114          | 0.1729 | 0.1673 | 0.2547 | 0.7453 | 55606 | 6443          | 2538      | 2187       | 0.1342 |
| 0.3888        | 4.0   | 5828  | 0.4169          | 0.1729 | 0.1671 | 0.2533 | 0.7467 | 55683 | 6347          | 2557      | 2264       | 0.1357 |
| 0.3647        | 5.0   | 7285  | 0.4178          | 0.1728 | 0.1666 | 0.2528 | 0.7472 | 55832 | 6358          | 2397      | 2403       | 0.1364 |
| 0.3226        | 6.0   | 8742  | 0.4199          | 0.1703 | 0.1648 | 0.2507 | 0.7493 | 55715 | 6304          | 2568      | 2125       | 0.1358 |
| 0.3045        | 7.0   | 10199 | 0.4309          | 0.1711 | 0.1653 | 0.2513 | 0.7487 | 55793 | 6322          | 2472      | 2257       | 0.1360 |
| 0.32          | 8.0   | 11656 | 0.4301          | 0.1714 | 0.1656 | 0.2518 | 0.7482 | 55768 | 6343          | 2476      | 2251       | 0.1341 |
| 0.2809        | 9.0   | 13113 | 0.4371          | 0.1706 | 0.1649 | 0.2513 | 0.7487 | 55774 | 6355          | 2458      | 2203       | 0.1333 |
| 0.2726        | 10.0  | 14570 | 0.4393          | 0.1715 | 0.1657 | 0.2520 | 0.7480 | 55766 | 6346          | 2475      | 2256       | 0.1352 |


### Framework versions

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