|
--- |
|
license: cc-by-sa-4.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- te_dx_jp |
|
model-index: |
|
- name: t5-base-TEDxJP-6front-1body-6rear |
|
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-6front-1body-6rear |
|
|
|
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: 0.4394 |
|
- Wer: 0.1704 |
|
- Mer: 0.1647 |
|
- Wil: 0.2508 |
|
- Wip: 0.7492 |
|
- Hits: 55836 |
|
- Substitutions: 6340 |
|
- Deletions: 2411 |
|
- Insertions: 2256 |
|
- Cer: 0.1351 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:| |
|
| 0.6164 | 1.0 | 1457 | 0.4627 | 0.2224 | 0.2073 | 0.2961 | 0.7039 | 54939 | 6736 | 2912 | 4716 | 0.1954 | |
|
| 0.5064 | 2.0 | 2914 | 0.4222 | 0.1785 | 0.1722 | 0.2591 | 0.7409 | 55427 | 6402 | 2758 | 2370 | 0.1416 | |
|
| 0.4909 | 3.0 | 4371 | 0.4147 | 0.1717 | 0.1664 | 0.2514 | 0.7486 | 55563 | 6218 | 2806 | 2068 | 0.1350 | |
|
| 0.4365 | 4.0 | 5828 | 0.4120 | 0.1722 | 0.1661 | 0.2525 | 0.7475 | 55848 | 6373 | 2366 | 2385 | 0.1380 | |
|
| 0.3954 | 5.0 | 7285 | 0.4145 | 0.1715 | 0.1655 | 0.2517 | 0.7483 | 55861 | 6355 | 2371 | 2351 | 0.1384 | |
|
| 0.3181 | 6.0 | 8742 | 0.4178 | 0.1710 | 0.1650 | 0.2509 | 0.7491 | 55891 | 6326 | 2370 | 2348 | 0.1368 | |
|
| 0.2971 | 7.0 | 10199 | 0.4261 | 0.1698 | 0.1640 | 0.2497 | 0.7503 | 55900 | 6304 | 2383 | 2279 | 0.1348 | |
|
| 0.2754 | 8.0 | 11656 | 0.4299 | 0.1703 | 0.1645 | 0.2504 | 0.7496 | 55875 | 6320 | 2392 | 2288 | 0.1354 | |
|
| 0.2604 | 9.0 | 13113 | 0.4371 | 0.1702 | 0.1644 | 0.2506 | 0.7494 | 55864 | 6343 | 2380 | 2267 | 0.1347 | |
|
| 0.2477 | 10.0 | 14570 | 0.4394 | 0.1704 | 0.1647 | 0.2508 | 0.7492 | 55836 | 6340 | 2411 | 2256 | 0.1351 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.2 |
|
- Pytorch 1.12.1+cu116 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
