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---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-8front-1body-8rear
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-8front-1body-8rear
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: 0.4383
- Wer: 0.1703
- Mer: 0.1643
- Wil: 0.2498
- Wip: 0.7502
- Hits: 55917
- Substitutions: 6285
- Deletions: 2385
- Insertions: 2327
- Cer: 0.1338
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.5634 | 1.0 | 1457 | 0.4668 | 0.2271 | 0.2101 | 0.2986 | 0.7014 | 55139 | 6756 | 2692 | 5219 | 0.1993 |
| 0.5335 | 2.0 | 2914 | 0.4168 | 0.1852 | 0.1776 | 0.2649 | 0.7351 | 55407 | 6467 | 2713 | 2782 | 0.1495 |
| 0.4453 | 3.0 | 4371 | 0.4124 | 0.1738 | 0.1678 | 0.2545 | 0.7455 | 55683 | 6391 | 2513 | 2321 | 0.1344 |
| 0.388 | 4.0 | 5828 | 0.4082 | 0.1703 | 0.1646 | 0.2502 | 0.7498 | 55838 | 6297 | 2452 | 2249 | 0.1324 |
| 0.3448 | 5.0 | 7285 | 0.4156 | 0.1704 | 0.1646 | 0.2505 | 0.7495 | 55840 | 6320 | 2427 | 2257 | 0.1339 |
| 0.3103 | 6.0 | 8742 | 0.4177 | 0.1690 | 0.1632 | 0.2484 | 0.7516 | 55955 | 6263 | 2369 | 2280 | 0.1324 |
| 0.3369 | 7.0 | 10199 | 0.4225 | 0.1688 | 0.1631 | 0.2480 | 0.7520 | 55930 | 6230 | 2427 | 2244 | 0.1327 |
| 0.3127 | 8.0 | 11656 | 0.4294 | 0.1692 | 0.1636 | 0.2489 | 0.7511 | 55876 | 6265 | 2446 | 2220 | 0.1331 |
| 0.2739 | 9.0 | 13113 | 0.4329 | 0.1702 | 0.1643 | 0.2501 | 0.7499 | 55903 | 6316 | 2368 | 2307 | 0.1338 |
| 0.269 | 10.0 | 14570 | 0.4383 | 0.1703 | 0.1643 | 0.2498 | 0.7502 | 55917 | 6285 | 2385 | 2327 | 0.1338 |
### Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1
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