---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-0front-1body-6rear
  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-0front-1body-6rear

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: 0.4698
- Wer: 0.1756
- Mer: 0.1696
- Wil: 0.2578
- Wip: 0.7422
- Hits: 55507
- Substitutions: 6509
- Deletions: 2571
- Insertions: 2259
- Cer: 0.1373

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.6157        | 1.0   | 1457  | 0.4985          | 0.2141 | 0.2018 | 0.2933 | 0.7067 | 54712 | 6913          | 2962      | 3955       | 0.1920 |
| 0.5098        | 2.0   | 2914  | 0.4500          | 0.1847 | 0.1781 | 0.2663 | 0.7337 | 55040 | 6505          | 3042      | 2383       | 0.1473 |
| 0.4729        | 3.0   | 4371  | 0.4424          | 0.1768 | 0.1709 | 0.2591 | 0.7409 | 55397 | 6509          | 2681      | 2227       | 0.1386 |
| 0.4284        | 4.0   | 5828  | 0.4473          | 0.1753 | 0.1696 | 0.2573 | 0.7427 | 55457 | 6461          | 2669      | 2194       | 0.1362 |
| 0.394         | 5.0   | 7285  | 0.4462          | 0.1795 | 0.1729 | 0.2612 | 0.7388 | 55459 | 6530          | 2598      | 2468       | 0.1484 |
| 0.3556        | 6.0   | 8742  | 0.4521          | 0.1759 | 0.1700 | 0.2579 | 0.7421 | 55449 | 6480          | 2658      | 2221       | 0.1365 |
| 0.3348        | 7.0   | 10199 | 0.4588          | 0.1742 | 0.1686 | 0.2567 | 0.7433 | 55491 | 6491          | 2605      | 2156       | 0.1358 |
| 0.3594        | 8.0   | 11656 | 0.4608          | 0.1755 | 0.1697 | 0.2580 | 0.7420 | 55468 | 6516          | 2603      | 2215       | 0.1371 |
| 0.3065        | 9.0   | 13113 | 0.4685          | 0.1758 | 0.1698 | 0.2580 | 0.7420 | 55496 | 6510          | 2581      | 2263       | 0.1373 |
| 0.2976        | 10.0  | 14570 | 0.4698          | 0.1756 | 0.1696 | 0.2578 | 0.7422 | 55507 | 6509          | 2571      | 2259       | 0.1373 |


### Framework versions

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