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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: 0.4705
- Wer: 0.1772
- Mer: 0.1711
- Wil: 0.2598
- Wip: 0.7402
- Hits: 55441
- Substitutions: 6558
- Deletions: 2588
- Insertions: 2296
- Cer: 0.1388
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.6067 | 1.0 | 1457 | 0.4967 | 0.2034 | 0.1934 | 0.2844 | 0.7156 | 54800 | 6821 | 2966 | 3351 | 0.1679 |
| 0.579 | 2.0 | 2914 | 0.4534 | 0.1882 | 0.1805 | 0.2697 | 0.7303 | 55162 | 6619 | 2806 | 2728 | 0.1546 |
| 0.4934 | 3.0 | 4371 | 0.4463 | 0.1768 | 0.1710 | 0.2592 | 0.7408 | 55362 | 6496 | 2729 | 2197 | 0.1396 |
| 0.4371 | 4.0 | 5828 | 0.4444 | 0.1766 | 0.1707 | 0.2580 | 0.7420 | 55381 | 6417 | 2789 | 2197 | 0.1387 |
| 0.3917 | 5.0 | 7285 | 0.4450 | 0.1771 | 0.1711 | 0.2595 | 0.7405 | 55415 | 6520 | 2652 | 2269 | 0.1389 |
| 0.3614 | 6.0 | 8742 | 0.4516 | 0.1775 | 0.1714 | 0.2592 | 0.7408 | 55443 | 6481 | 2663 | 2323 | 0.1379 |
| 0.375 | 7.0 | 10199 | 0.4568 | 0.1777 | 0.1715 | 0.2593 | 0.7407 | 55418 | 6475 | 2694 | 2306 | 0.1396 |
| 0.3615 | 8.0 | 11656 | 0.4622 | 0.1764 | 0.1706 | 0.2585 | 0.7415 | 55380 | 6472 | 2735 | 2188 | 0.1382 |
| 0.3129 | 9.0 | 13113 | 0.4678 | 0.1770 | 0.1709 | 0.2592 | 0.7408 | 55474 | 6524 | 2589 | 2318 | 0.1385 |
| 0.3082 | 10.0 | 14570 | 0.4705 | 0.1772 | 0.1711 | 0.2598 | 0.7402 | 55441 | 6558 | 2588 | 2296 | 0.1388 |
### Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1
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