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---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-0front-1body-10rear-order-RB
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-10rear-order-RB
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: 0.4714
- Wer: 0.1751
- Mer: 0.1694
- Wil: 0.2572
- Wip: 0.7428
- Hits: 55476
- Substitutions: 6473
- Deletions: 2638
- Insertions: 2201
- Cer: 0.1381
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.6116 | 1.0 | 1457 | 0.4923 | 0.2289 | 0.2127 | 0.3015 | 0.6985 | 54722 | 6733 | 3132 | 4917 | 0.1992 |
| 0.5362 | 2.0 | 2914 | 0.4506 | 0.1835 | 0.1770 | 0.2661 | 0.7339 | 55105 | 6590 | 2892 | 2369 | 0.1447 |
| 0.4869 | 3.0 | 4371 | 0.4459 | 0.1806 | 0.1742 | 0.2629 | 0.7371 | 55298 | 6556 | 2733 | 2374 | 0.1424 |
| 0.4642 | 4.0 | 5828 | 0.4413 | 0.1767 | 0.1710 | 0.2588 | 0.7412 | 55331 | 6462 | 2794 | 2157 | 0.1379 |
| 0.4395 | 5.0 | 7285 | 0.4462 | 0.1779 | 0.1719 | 0.2594 | 0.7406 | 55367 | 6451 | 2769 | 2270 | 0.1391 |
| 0.3831 | 6.0 | 8742 | 0.4493 | 0.1751 | 0.1696 | 0.2568 | 0.7432 | 55370 | 6409 | 2808 | 2092 | 0.1369 |
| 0.3446 | 7.0 | 10199 | 0.4563 | 0.1769 | 0.1710 | 0.2595 | 0.7405 | 55401 | 6535 | 2651 | 2238 | 0.1397 |
| 0.3031 | 8.0 | 11656 | 0.4657 | 0.1754 | 0.1697 | 0.2578 | 0.7422 | 55436 | 6492 | 2659 | 2179 | 0.1372 |
| 0.3406 | 9.0 | 13113 | 0.4677 | 0.1750 | 0.1692 | 0.2570 | 0.7430 | 55502 | 6474 | 2611 | 2219 | 0.1365 |
| 0.3067 | 10.0 | 14570 | 0.4714 | 0.1751 | 0.1694 | 0.2572 | 0.7428 | 55476 | 6473 | 2638 | 2201 | 0.1381 |
### Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1
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