---
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: 0.4398
- Wer: 0.1697
- Mer: 0.1641
- Wil: 0.2506
- Wip: 0.7494
- Hits: 55824
- Substitutions: 6360
- Deletions: 2403
- Insertions: 2197
- Cer: 0.1335

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.5976        | 1.0   | 1457  | 0.4725          | 0.2267 | 0.2107 | 0.2985 | 0.7015 | 54877 | 6654          | 3056      | 4935       | 0.2024 |
| 0.4849        | 2.0   | 2914  | 0.4229          | 0.1789 | 0.1726 | 0.2590 | 0.7410 | 55401 | 6358          | 2828      | 2371       | 0.1432 |
| 0.4632        | 3.0   | 4371  | 0.4167          | 0.1725 | 0.1667 | 0.2529 | 0.7471 | 55723 | 6347          | 2517      | 2280       | 0.1343 |
| 0.3981        | 4.0   | 5828  | 0.4146          | 0.1716 | 0.1658 | 0.2521 | 0.7479 | 55784 | 6355          | 2448      | 2282       | 0.1336 |
| 0.3551        | 5.0   | 7285  | 0.4189          | 0.1713 | 0.1652 | 0.2512 | 0.7488 | 55909 | 6340          | 2338      | 2388       | 0.1345 |
| 0.3253        | 6.0   | 8742  | 0.4238          | 0.1714 | 0.1656 | 0.2514 | 0.7486 | 55805 | 6315          | 2467      | 2291       | 0.1359 |
| 0.308         | 7.0   | 10199 | 0.4292          | 0.1703 | 0.1645 | 0.2506 | 0.7494 | 55862 | 6341          | 2384      | 2271       | 0.1353 |
| 0.324         | 8.0   | 11656 | 0.4304          | 0.1693 | 0.1637 | 0.2497 | 0.7503 | 55856 | 6324          | 2407      | 2205       | 0.1336 |
| 0.2861        | 9.0   | 13113 | 0.4356          | 0.1694 | 0.1639 | 0.2501 | 0.7499 | 55814 | 6336          | 2437      | 2166       | 0.1332 |
| 0.2788        | 10.0  | 14570 | 0.4398          | 0.1697 | 0.1641 | 0.2506 | 0.7494 | 55824 | 6360          | 2403      | 2197       | 0.1335 |


### Framework versions

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