---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-4front-1body-4rear
  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-4front-1body-4rear

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: 0.4419
- Wer: 0.1696
- Mer: 0.1638
- Wil: 0.2494
- Wip: 0.7506
- Hits: 55898
- Substitutions: 6290
- Deletions: 2399
- Insertions: 2262
- Cer: 0.1328

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.5923        | 1.0   | 1457  | 0.4757          | 0.2180 | 0.2043 | 0.2941 | 0.7059 | 54841 | 6796          | 2950      | 4332       | 0.1931 |
| 0.5311        | 2.0   | 2914  | 0.4278          | 0.1817 | 0.1745 | 0.2611 | 0.7389 | 55507 | 6397          | 2683      | 2656       | 0.1467 |
| 0.4511        | 3.0   | 4371  | 0.4187          | 0.1715 | 0.1659 | 0.2529 | 0.7471 | 55668 | 6395          | 2524      | 2157       | 0.1322 |
| 0.3544        | 4.0   | 5828  | 0.4179          | 0.1700 | 0.1644 | 0.2498 | 0.7502 | 55795 | 6272          | 2520      | 2185       | 0.1319 |
| 0.3649        | 5.0   | 7285  | 0.4210          | 0.1700 | 0.1645 | 0.2506 | 0.7494 | 55799 | 6334          | 2454      | 2195       | 0.1319 |
| 0.3622        | 6.0   | 8742  | 0.4223          | 0.1706 | 0.1649 | 0.2503 | 0.7497 | 55823 | 6278          | 2486      | 2256       | 0.1358 |
| 0.3286        | 7.0   | 10199 | 0.4258          | 0.1692 | 0.1638 | 0.2492 | 0.7508 | 55807 | 6273          | 2507      | 2149       | 0.1325 |
| 0.3069        | 8.0   | 11656 | 0.4307          | 0.1697 | 0.1640 | 0.2493 | 0.7507 | 55861 | 6265          | 2461      | 2232       | 0.1329 |
| 0.2776        | 9.0   | 13113 | 0.4403          | 0.1697 | 0.1640 | 0.2497 | 0.7503 | 55883 | 6304          | 2400      | 2257       | 0.1328 |
| 0.3175        | 10.0  | 14570 | 0.4419          | 0.1696 | 0.1638 | 0.2494 | 0.7506 | 55898 | 6290          | 2399      | 2262       | 0.1328 |


### Framework versions

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