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---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-4front-1body-4rear
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-4front-1body-4rear
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: 0.4413
- Wer: 0.1701
- Mer: 0.1644
- Wil: 0.2507
- Wip: 0.7493
- Hits: 55851
- Substitutions: 6351
- Deletions: 2385
- Insertions: 2250
- Cer: 0.1341
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.6042 | 1.0 | 1457 | 0.4733 | 0.2042 | 0.1938 | 0.2829 | 0.7171 | 54861 | 6662 | 3064 | 3461 | 0.1725 |
| 0.5747 | 2.0 | 2914 | 0.4297 | 0.1812 | 0.1744 | 0.2610 | 0.7390 | 55403 | 6393 | 2791 | 2517 | 0.1458 |
| 0.4509 | 3.0 | 4371 | 0.4187 | 0.1751 | 0.1686 | 0.2557 | 0.7443 | 55743 | 6433 | 2411 | 2464 | 0.1393 |
| 0.4216 | 4.0 | 5828 | 0.4133 | 0.1715 | 0.1656 | 0.2515 | 0.7485 | 55811 | 6324 | 2452 | 2301 | 0.1346 |
| 0.356 | 5.0 | 7285 | 0.4219 | 0.1703 | 0.1649 | 0.2502 | 0.7498 | 55717 | 6262 | 2608 | 2129 | 0.1327 |
| 0.3174 | 6.0 | 8742 | 0.4232 | 0.1700 | 0.1642 | 0.2494 | 0.7506 | 55863 | 6253 | 2471 | 2253 | 0.1331 |
| 0.2992 | 7.0 | 10199 | 0.4309 | 0.1701 | 0.1647 | 0.2511 | 0.7489 | 55746 | 6350 | 2491 | 2148 | 0.1332 |
| 0.307 | 8.0 | 11656 | 0.4317 | 0.1699 | 0.1644 | 0.2505 | 0.7495 | 55801 | 6331 | 2455 | 2189 | 0.1336 |
| 0.2692 | 9.0 | 13113 | 0.4385 | 0.1699 | 0.1643 | 0.2504 | 0.7496 | 55834 | 6334 | 2419 | 2223 | 0.1346 |
| 0.2965 | 10.0 | 14570 | 0.4413 | 0.1701 | 0.1644 | 0.2507 | 0.7493 | 55851 | 6351 | 2385 | 2250 | 0.1341 |
### Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1