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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-2context
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-2context
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: 0.4968
- Wer: 0.1969
- Mer: 0.1895
- Wil: 0.2801
- Wip: 0.7199
- Hits: 55902
- Substitutions: 6899
- Deletions: 3570
- Insertions: 2599
- Cer: 0.1727
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
| 0.7136 | 1.0 | 746 | 0.5716 | 0.2512 | 0.2345 | 0.3279 | 0.6721 | 54430 | 7249 | 4692 | 4731 | 0.2344 |
| 0.6267 | 2.0 | 1492 | 0.5152 | 0.2088 | 0.2005 | 0.2917 | 0.7083 | 55245 | 6949 | 4177 | 2732 | 0.2009 |
| 0.5416 | 3.0 | 2238 | 0.4969 | 0.2025 | 0.1948 | 0.2851 | 0.7149 | 55575 | 6871 | 3925 | 2646 | 0.1802 |
| 0.5223 | 4.0 | 2984 | 0.4915 | 0.1989 | 0.1917 | 0.2816 | 0.7184 | 55652 | 6826 | 3893 | 2481 | 0.1754 |
| 0.4985 | 5.0 | 3730 | 0.4929 | 0.1991 | 0.1916 | 0.2814 | 0.7186 | 55759 | 6828 | 3784 | 2603 | 0.1753 |
| 0.4675 | 6.0 | 4476 | 0.4910 | 0.1969 | 0.1897 | 0.2799 | 0.7201 | 55834 | 6859 | 3678 | 2534 | 0.1756 |
| 0.445 | 7.0 | 5222 | 0.4940 | 0.1955 | 0.1884 | 0.2782 | 0.7218 | 55881 | 6821 | 3669 | 2485 | 0.1712 |
| 0.4404 | 8.0 | 5968 | 0.4932 | 0.1979 | 0.1903 | 0.2801 | 0.7199 | 55881 | 6828 | 3662 | 2643 | 0.1742 |
| 0.4525 | 9.0 | 6714 | 0.4951 | 0.1968 | 0.1893 | 0.2799 | 0.7201 | 55939 | 6897 | 3535 | 2632 | 0.1740 |
| 0.4077 | 10.0 | 7460 | 0.4968 | 0.1969 | 0.1895 | 0.2801 | 0.7199 | 55902 | 6899 | 3570 | 2599 | 0.1727 |
### Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu102
- Datasets 1.15.1
- Tokenizers 0.10.3
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