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---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-7front-1body-7rear
  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-7front-1body-7rear

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: 0.4385
- Wer: 0.1688
- Mer: 0.1632
- Wil: 0.2486
- Wip: 0.7514
- Hits: 55895
- Substitutions: 6273
- Deletions: 2419
- Insertions: 2208
- Cer: 0.1334

## 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: 10
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.5657        | 1.0   | 1457  | 0.4744          | 0.2212 | 0.2056 | 0.2946 | 0.7054 | 55195 | 6783          | 2609      | 4892       | 0.1922 |
| 0.5388        | 2.0   | 2914  | 0.4193          | 0.1791 | 0.1724 | 0.2601 | 0.7399 | 55526 | 6485          | 2576      | 2507       | 0.1404 |
| 0.447         | 3.0   | 4371  | 0.4119          | 0.1728 | 0.1670 | 0.2531 | 0.7469 | 55690 | 6334          | 2563      | 2266       | 0.1341 |
| 0.3952        | 4.0   | 5828  | 0.4088          | 0.1704 | 0.1647 | 0.2503 | 0.7497 | 55802 | 6283          | 2502      | 2220       | 0.1330 |
| 0.3498        | 5.0   | 7285  | 0.4138          | 0.1701 | 0.1643 | 0.2500 | 0.7500 | 55881 | 6305          | 2401      | 2280       | 0.1321 |
| 0.3107        | 6.0   | 8742  | 0.4201          | 0.1693 | 0.1636 | 0.2497 | 0.7503 | 55888 | 6334          | 2365      | 2236       | 0.1319 |
| 0.3443        | 7.0   | 10199 | 0.4239          | 0.1694 | 0.1637 | 0.2495 | 0.7505 | 55890 | 6309          | 2388      | 2241       | 0.1328 |
| 0.3099        | 8.0   | 11656 | 0.4316          | 0.1695 | 0.1639 | 0.2496 | 0.7504 | 55833 | 6292          | 2462      | 2192       | 0.1337 |
| 0.2804        | 9.0   | 13113 | 0.4345          | 0.1687 | 0.1631 | 0.2486 | 0.7514 | 55896 | 6273          | 2418      | 2206       | 0.1332 |
| 0.2714        | 10.0  | 14570 | 0.4385          | 0.1688 | 0.1632 | 0.2486 | 0.7514 | 55895 | 6273          | 2419      | 2208       | 0.1334 |


### Framework versions

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