---
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: 0.4413
- Wer: 0.1701
- Mer: 0.1644
- Wil: 0.2507
- Wip: 0.7493
- Hits: 55851
- Substitutions: 6351
- Deletions: 2385
- Insertions: 2250
- Cer: 0.1341

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.6042        | 1.0   | 1457  | 0.4733          | 0.2042 | 0.1938 | 0.2829 | 0.7171 | 54861 | 6662          | 3064      | 3461       | 0.1725 |
| 0.5747        | 2.0   | 2914  | 0.4297          | 0.1812 | 0.1744 | 0.2610 | 0.7390 | 55403 | 6393          | 2791      | 2517       | 0.1458 |
| 0.4509        | 3.0   | 4371  | 0.4187          | 0.1751 | 0.1686 | 0.2557 | 0.7443 | 55743 | 6433          | 2411      | 2464       | 0.1393 |
| 0.4216        | 4.0   | 5828  | 0.4133          | 0.1715 | 0.1656 | 0.2515 | 0.7485 | 55811 | 6324          | 2452      | 2301       | 0.1346 |
| 0.356         | 5.0   | 7285  | 0.4219          | 0.1703 | 0.1649 | 0.2502 | 0.7498 | 55717 | 6262          | 2608      | 2129       | 0.1327 |
| 0.3174        | 6.0   | 8742  | 0.4232          | 0.1700 | 0.1642 | 0.2494 | 0.7506 | 55863 | 6253          | 2471      | 2253       | 0.1331 |
| 0.2992        | 7.0   | 10199 | 0.4309          | 0.1701 | 0.1647 | 0.2511 | 0.7489 | 55746 | 6350          | 2491      | 2148       | 0.1332 |
| 0.307         | 8.0   | 11656 | 0.4317          | 0.1699 | 0.1644 | 0.2505 | 0.7495 | 55801 | 6331          | 2455      | 2189       | 0.1336 |
| 0.2692        | 9.0   | 13113 | 0.4385          | 0.1699 | 0.1643 | 0.2504 | 0.7496 | 55834 | 6334          | 2419      | 2223       | 0.1346 |
| 0.2965        | 10.0  | 14570 | 0.4413          | 0.1701 | 0.1644 | 0.2507 | 0.7493 | 55851 | 6351          | 2385      | 2250       | 0.1341 |


### Framework versions

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