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---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-1body-3context
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-1body-3context
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: 0.4926
- Wer: 0.1968
- Mer: 0.1894
- Wil: 0.2793
- Wip: 0.7207
- Hits: 55899
- Substitutions: 6836
- Deletions: 3636
- Insertions: 2590
- Cer: 0.1733
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.7082 | 1.0 | 746 | 0.5637 | 0.2626 | 0.2430 | 0.3355 | 0.6645 | 54301 | 7195 | 4875 | 5358 | 0.2552 |
| 0.6213 | 2.0 | 1492 | 0.5150 | 0.2068 | 0.1994 | 0.2899 | 0.7101 | 55107 | 6861 | 4403 | 2462 | 0.1866 |
| 0.5331 | 3.0 | 2238 | 0.4945 | 0.2038 | 0.1958 | 0.2858 | 0.7142 | 55551 | 6845 | 3975 | 2705 | 0.1816 |
| 0.5185 | 4.0 | 2984 | 0.4880 | 0.2003 | 0.1929 | 0.2831 | 0.7169 | 55639 | 6860 | 3872 | 2563 | 0.1779 |
| 0.4963 | 5.0 | 3730 | 0.4858 | 0.1988 | 0.1912 | 0.2810 | 0.7190 | 55837 | 6838 | 3696 | 2662 | 0.1772 |
| 0.4625 | 6.0 | 4476 | 0.4885 | 0.1964 | 0.1894 | 0.2799 | 0.7201 | 55785 | 6875 | 3711 | 2448 | 0.1720 |
| 0.4416 | 7.0 | 5222 | 0.4898 | 0.1962 | 0.1890 | 0.2788 | 0.7212 | 55870 | 6819 | 3682 | 2522 | 0.1726 |
| 0.4287 | 8.0 | 5968 | 0.4894 | 0.1968 | 0.1894 | 0.2790 | 0.7210 | 55889 | 6804 | 3678 | 2580 | 0.1743 |
| 0.4457 | 9.0 | 6714 | 0.4909 | 0.1964 | 0.1891 | 0.2792 | 0.7208 | 55919 | 6858 | 3594 | 2586 | 0.1739 |
| 0.4068 | 10.0 | 7460 | 0.4926 | 0.1968 | 0.1894 | 0.2793 | 0.7207 | 55899 | 6836 | 3636 | 2590 | 0.1733 |
### Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu102
- Datasets 1.15.1
- Tokenizers 0.10.3
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