---
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: 0.4373
- Wer: 0.1699
- Mer: 0.1642
- Wil: 0.2499
- Wip: 0.7501
- Hits: 55848
- Substitutions: 6297
- Deletions: 2442
- Insertions: 2236
- Cer: 0.1360

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.5812        | 1.0   | 1457  | 0.4658          | 0.2393 | 0.2197 | 0.3076 | 0.6924 | 54882 | 6717          | 2988      | 5750       | 0.2187 |
| 0.5253        | 2.0   | 2914  | 0.4264          | 0.1832 | 0.1756 | 0.2632 | 0.7368 | 55549 | 6498          | 2540      | 2793       | 0.1520 |
| 0.4412        | 3.0   | 4371  | 0.4161          | 0.1728 | 0.1670 | 0.2535 | 0.7465 | 55665 | 6363          | 2559      | 2240       | 0.1360 |
| 0.3465        | 4.0   | 5828  | 0.4155          | 0.1706 | 0.1650 | 0.2504 | 0.7496 | 55756 | 6266          | 2565      | 2186       | 0.1356 |
| 0.3575        | 5.0   | 7285  | 0.4196          | 0.1696 | 0.1642 | 0.2498 | 0.7502 | 55781 | 6283          | 2523      | 2151       | 0.1358 |
| 0.3556        | 6.0   | 8742  | 0.4164          | 0.1687 | 0.1632 | 0.2487 | 0.7513 | 55857 | 6274          | 2456      | 2167       | 0.1341 |
| 0.3145        | 7.0   | 10199 | 0.4245          | 0.1705 | 0.1648 | 0.2504 | 0.7496 | 55819 | 6297          | 2471      | 2244       | 0.1355 |
| 0.3074        | 8.0   | 11656 | 0.4266          | 0.1693 | 0.1639 | 0.2494 | 0.7506 | 55799 | 6274          | 2514      | 2148       | 0.1358 |
| 0.269         | 9.0   | 13113 | 0.4352          | 0.1693 | 0.1637 | 0.2492 | 0.7508 | 55878 | 6288          | 2421      | 2225       | 0.1346 |
| 0.3162        | 10.0  | 14570 | 0.4373          | 0.1699 | 0.1642 | 0.2499 | 0.7501 | 55848 | 6297          | 2442      | 2236       | 0.1360 |


### Framework versions

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