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---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-6front-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-6front-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: 0.4380
- Wer: 0.1700
- Mer: 0.1642
- Wil: 0.2501
- Wip: 0.7499
- Hits: 55894
- Substitutions: 6327
- Deletions: 2366
- Insertions: 2286
- Cer: 0.1345
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.5938 | 1.0 | 1457 | 0.4764 | 0.2123 | 0.1997 | 0.2886 | 0.7114 | 54961 | 6701 | 2925 | 4085 | 0.1721 |
| 0.4817 | 2.0 | 2914 | 0.4166 | 0.1827 | 0.1754 | 0.2615 | 0.7385 | 55462 | 6356 | 2769 | 2676 | 0.1470 |
| 0.4467 | 3.0 | 4371 | 0.4119 | 0.1715 | 0.1660 | 0.2530 | 0.7470 | 55677 | 6410 | 2500 | 2169 | 0.1339 |
| 0.3818 | 4.0 | 5828 | 0.4134 | 0.1714 | 0.1654 | 0.2522 | 0.7478 | 55837 | 6396 | 2354 | 2319 | 0.1340 |
| 0.3577 | 5.0 | 7285 | 0.4171 | 0.1716 | 0.1653 | 0.2509 | 0.7491 | 55938 | 6303 | 2346 | 2432 | 0.1339 |
| 0.3222 | 6.0 | 8742 | 0.4195 | 0.1681 | 0.1628 | 0.2484 | 0.7516 | 55829 | 6282 | 2476 | 2099 | 0.1314 |
| 0.2938 | 7.0 | 10199 | 0.4242 | 0.1685 | 0.1634 | 0.2489 | 0.7511 | 55753 | 6267 | 2567 | 2052 | 0.1327 |
| 0.3174 | 8.0 | 11656 | 0.4269 | 0.1676 | 0.1624 | 0.2482 | 0.7518 | 55846 | 6299 | 2442 | 2083 | 0.1326 |
| 0.277 | 9.0 | 13113 | 0.4332 | 0.1700 | 0.1644 | 0.2505 | 0.7495 | 55831 | 6331 | 2425 | 2227 | 0.1346 |
| 0.2625 | 10.0 | 14570 | 0.4380 | 0.1700 | 0.1642 | 0.2501 | 0.7499 | 55894 | 6327 | 2366 | 2286 | 0.1345 |
### Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1
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