|
--- |
|
license: cc-by-sa-4.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- te_dx_jp |
|
model-index: |
|
- name: t5-base-TEDxJP-11body-0context |
|
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-11body-0context |
|
|
|
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: 0.8068 |
|
- Wer: 0.1976 |
|
- Mer: 0.1904 |
|
- Wil: 0.2816 |
|
- Wip: 0.7184 |
|
- Hits: 602335 |
|
- Substitutions: 75050 |
|
- Deletions: 39435 |
|
- Insertions: 27185 |
|
- Cer: 0.1625 |
|
|
|
## 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: 64 |
|
- eval_batch_size: 8 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:------:|:-------------:|:---------:|:----------:|:------:| |
|
| 0.8909 | 1.0 | 746 | 0.7722 | 0.3120 | 0.2861 | 0.3989 | 0.6011 | 558138 | 99887 | 58795 | 64983 | 0.2652 | |
|
| 0.6786 | 2.0 | 1492 | 0.7021 | 0.2226 | 0.2122 | 0.3069 | 0.6931 | 592242 | 78773 | 45805 | 34978 | 0.1862 | |
|
| 0.5627 | 3.0 | 2238 | 0.6996 | 0.2104 | 0.2016 | 0.2942 | 0.7058 | 597381 | 76593 | 42846 | 31392 | 0.1752 | |
|
| 0.489 | 4.0 | 2984 | 0.7161 | 0.2030 | 0.1952 | 0.2865 | 0.7135 | 599808 | 75155 | 41857 | 28506 | 0.1684 | |
|
| 0.4355 | 5.0 | 3730 | 0.7389 | 0.2000 | 0.1924 | 0.2837 | 0.7163 | 601815 | 75247 | 39758 | 28335 | 0.1651 | |
|
| 0.3836 | 6.0 | 4476 | 0.7537 | 0.1992 | 0.1918 | 0.2829 | 0.7171 | 601846 | 75046 | 39928 | 27815 | 0.1640 | |
|
| 0.3617 | 7.0 | 5222 | 0.7743 | 0.1995 | 0.1918 | 0.2832 | 0.7168 | 602287 | 75268 | 39265 | 28445 | 0.1642 | |
|
| 0.3258 | 8.0 | 5968 | 0.7907 | 0.1971 | 0.1899 | 0.2809 | 0.7191 | 602800 | 74887 | 39133 | 27258 | 0.1620 | |
|
| 0.3225 | 9.0 | 6714 | 0.8035 | 0.1981 | 0.1908 | 0.2823 | 0.7177 | 602418 | 75372 | 39030 | 27625 | 0.1630 | |
|
| 0.3162 | 10.0 | 7460 | 0.8068 | 0.1976 | 0.1904 | 0.2816 | 0.7184 | 602335 | 75050 | 39435 | 27185 | 0.1625 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.12.5 |
|
- Pytorch 1.10.0+cu102 |
|
- Datasets 1.15.1 |
|
- Tokenizers 0.10.3 |
|
|
