---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-8front-1body-8rear
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-base-TEDxJP-8front-1body-8rear

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: 0.4357
- Wer: 0.1706
- Mer: 0.1649
- Wil: 0.2512
- Wip: 0.7488
- Hits: 55798
- Substitutions: 6352
- Deletions: 2437
- Insertions: 2230
- Cer: 0.1344

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.585         | 1.0   | 1457  | 0.4589          | 0.2109 | 0.1988 | 0.2866 | 0.7134 | 54910 | 6576          | 3101      | 3947       | 0.1850 |
| 0.5098        | 2.0   | 2914  | 0.4190          | 0.1814 | 0.1744 | 0.2618 | 0.7382 | 55486 | 6473          | 2628      | 2617       | 0.1435 |
| 0.4648        | 3.0   | 4371  | 0.4108          | 0.1728 | 0.1669 | 0.2526 | 0.7474 | 55696 | 6298          | 2593      | 2267       | 0.1366 |
| 0.4075        | 4.0   | 5828  | 0.4071          | 0.1728 | 0.1670 | 0.2534 | 0.7466 | 55649 | 6356          | 2582      | 2220       | 0.1364 |
| 0.3904        | 5.0   | 7285  | 0.4118          | 0.1709 | 0.1652 | 0.2514 | 0.7486 | 55753 | 6334          | 2500      | 2203       | 0.1343 |
| 0.343         | 6.0   | 8742  | 0.4131          | 0.1701 | 0.1647 | 0.2509 | 0.7491 | 55741 | 6334          | 2512      | 2142       | 0.1338 |
| 0.2981        | 7.0   | 10199 | 0.4211          | 0.1701 | 0.1645 | 0.2503 | 0.7497 | 55788 | 6302          | 2497      | 2187       | 0.1345 |
| 0.2663        | 8.0   | 11656 | 0.4291          | 0.1698 | 0.1642 | 0.2503 | 0.7497 | 55851 | 6338          | 2398      | 2234       | 0.1339 |
| 0.2938        | 9.0   | 13113 | 0.4317          | 0.1699 | 0.1642 | 0.2503 | 0.7497 | 55833 | 6329          | 2425      | 2218       | 0.1340 |
| 0.2692        | 10.0  | 14570 | 0.4357          | 0.1706 | 0.1649 | 0.2512 | 0.7488 | 55798 | 6352          | 2437      | 2230       | 0.1344 |


### Framework versions

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