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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: 0.4749
- Wer: 0.1754
- Mer: 0.1696
- Wil: 0.2575
- Wip: 0.7425
- Hits: 55482
- Substitutions: 6478
- Deletions: 2627
- Insertions: 2225
- Cer: 0.1370
## 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: 40
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.637 | 1.0 | 1457 | 0.4932 | 0.2359 | 0.2179 | 0.3082 | 0.6918 | 54682 | 6909 | 2996 | 5331 | 0.2100 |
| 0.5501 | 2.0 | 2914 | 0.4572 | 0.1831 | 0.1766 | 0.2655 | 0.7345 | 55134 | 6575 | 2878 | 2370 | 0.1461 |
| 0.5505 | 3.0 | 4371 | 0.4470 | 0.1787 | 0.1728 | 0.2609 | 0.7391 | 55267 | 6494 | 2826 | 2222 | 0.1400 |
| 0.4921 | 4.0 | 5828 | 0.4426 | 0.1794 | 0.1730 | 0.2606 | 0.7394 | 55420 | 6468 | 2699 | 2423 | 0.1407 |
| 0.4465 | 5.0 | 7285 | 0.4507 | 0.1783 | 0.1721 | 0.2596 | 0.7404 | 55420 | 6458 | 2709 | 2351 | 0.1390 |
| 0.3557 | 6.0 | 8742 | 0.4567 | 0.1768 | 0.1708 | 0.2585 | 0.7415 | 55416 | 6459 | 2712 | 2245 | 0.1401 |
| 0.3367 | 7.0 | 10199 | 0.4613 | 0.1772 | 0.1709 | 0.2589 | 0.7411 | 55505 | 6497 | 2585 | 2363 | 0.1387 |
| 0.328 | 8.0 | 11656 | 0.4624 | 0.1769 | 0.1708 | 0.2587 | 0.7413 | 55442 | 6478 | 2667 | 2278 | 0.1383 |
| 0.2992 | 9.0 | 13113 | 0.4726 | 0.1764 | 0.1704 | 0.2580 | 0.7420 | 55461 | 6463 | 2663 | 2264 | 0.1378 |
| 0.2925 | 10.0 | 14570 | 0.4749 | 0.1754 | 0.1696 | 0.2575 | 0.7425 | 55482 | 6478 | 2627 | 2225 | 0.1370 |
### Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1
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