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---
license: apache-2.0
base_model: rinna/japanese-hubert-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hubert-rinnna-jp-jdrtsp-fw07sp-14
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. -->
# hubert-rinnna-jp-jdrtsp-fw07sp-14
This model is a fine-tuned version of [rinna/japanese-hubert-base](https://huggingface.co/rinna/japanese-hubert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1685
- Wer: 0.2927
- Cer: 0.1710
## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 4.4197 | 1.0 | 404 | 4.0767 | 0.9928 | 0.9960 |
| 2.8984 | 2.0 | 808 | 2.7950 | 0.9928 | 0.9960 |
| 2.1179 | 3.0 | 1212 | 1.9178 | 0.9928 | 0.9960 |
| 1.4282 | 4.0 | 1616 | 1.0854 | 0.6262 | 0.4791 |
| 1.0793 | 5.0 | 2020 | 0.7672 | 0.4996 | 0.2944 |
| 0.9064 | 6.0 | 2424 | 0.6212 | 0.4573 | 0.2737 |
| 0.8366 | 7.0 | 2828 | 0.5247 | 0.4132 | 0.2450 |
| 0.7425 | 8.0 | 3232 | 0.4502 | 0.3786 | 0.2257 |
| 0.7017 | 9.0 | 3636 | 0.3912 | 0.3509 | 0.2082 |
| 0.6275 | 10.0 | 4040 | 0.3407 | 0.3328 | 0.1979 |
| 0.5853 | 11.0 | 4444 | 0.3045 | 0.3226 | 0.1920 |
| 0.5551 | 12.0 | 4848 | 0.2657 | 0.3139 | 0.1865 |
| 0.5105 | 13.0 | 5252 | 0.2455 | 0.3086 | 0.1827 |
| 0.5073 | 14.0 | 5656 | 0.2389 | 0.3092 | 0.1832 |
| 0.4722 | 15.0 | 6060 | 0.2170 | 0.3030 | 0.1781 |
| 0.481 | 16.0 | 6464 | 0.2089 | 0.3023 | 0.1783 |
| 0.4738 | 17.0 | 6868 | 0.2002 | 0.3004 | 0.1763 |
| 0.4518 | 18.0 | 7272 | 0.1990 | 0.3006 | 0.1765 |
| 0.4402 | 19.0 | 7676 | 0.1900 | 0.2999 | 0.1764 |
| 0.4387 | 20.0 | 8080 | 0.1826 | 0.2970 | 0.1740 |
| 0.4212 | 21.0 | 8484 | 0.1767 | 0.2955 | 0.1733 |
| 0.3893 | 22.0 | 8888 | 0.1707 | 0.2937 | 0.1719 |
| 0.4055 | 23.0 | 9292 | 0.1704 | 0.2943 | 0.1723 |
| 0.394 | 24.0 | 9696 | 0.1684 | 0.2934 | 0.1716 |
| 0.3997 | 25.0 | 10100 | 0.1685 | 0.2927 | 0.1710 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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