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---
library_name: transformers
license: apache-2.0
base_model: rinna/japanese-hubert-base
tags:
- automatic-speech-recognition
- original_kakeiken_W_closed_add_ver2
- generated_from_trainer
metrics:
- wer
model-index:
- name: Hubert-kakeiken-W-closed_add_ver2
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-kakeiken-W-closed_add_ver2
This model is a fine-tuned version of [rinna/japanese-hubert-base](https://huggingface.co/rinna/japanese-hubert-base) on the ORIGINAL_KAKEIKEN_W_CLOSED_ADD_VER2 - JA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0617
- Wer: 0.9988
- Cer: 1.0129
## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 12500
- num_epochs: 40.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
| 28.4059 | 1.0 | 880 | 10.6721 | 1.0 | 1.1284 |
| 9.1792 | 2.0 | 1760 | 6.9924 | 1.0 | 1.1284 |
| 4.9143 | 3.0 | 2640 | 3.8166 | 1.0 | 1.1284 |
| 3.1394 | 4.0 | 3520 | 2.8829 | 1.0 | 1.1283 |
| 2.7266 | 5.0 | 4400 | 1.9608 | 1.0 | 1.1444 |
| 1.4314 | 6.0 | 5280 | 0.8434 | 0.9999 | 1.0662 |
| 0.6837 | 7.0 | 6160 | 0.4583 | 0.9997 | 1.0330 |
| 0.403 | 8.0 | 7040 | 0.2512 | 0.9991 | 1.0479 |
| 0.3035 | 9.0 | 7920 | 0.1972 | 0.9993 | 1.0365 |
| 0.229 | 10.0 | 8800 | 0.0872 | 0.9991 | 1.0264 |
| 0.1995 | 11.0 | 9680 | 0.0959 | 0.9988 | 1.0262 |
| 0.1824 | 12.0 | 10560 | 0.1012 | 0.9988 | 1.0317 |
| 0.1774 | 13.0 | 11440 | 0.0541 | 0.9991 | 1.0220 |
| 0.1739 | 14.0 | 12320 | 0.0703 | 0.9990 | 1.0270 |
| 0.1609 | 15.0 | 13200 | 0.0480 | 0.9988 | 1.0203 |
| 0.1512 | 16.0 | 14080 | 0.0540 | 0.9988 | 1.0162 |
| 0.1412 | 17.0 | 14960 | 0.0396 | 0.9988 | 1.0188 |
| 0.1391 | 18.0 | 15840 | 0.0493 | 0.9988 | 1.0195 |
| 0.1325 | 19.0 | 16720 | 0.0366 | 0.9988 | 1.0186 |
| 0.1242 | 20.0 | 17600 | 0.0392 | 0.9988 | 1.0178 |
| 0.122 | 21.0 | 18480 | 0.0545 | 0.9988 | 1.0193 |
| 0.1143 | 22.0 | 19360 | 0.0408 | 0.9988 | 1.0185 |
| 0.1087 | 23.0 | 20240 | 0.0310 | 0.9988 | 1.0176 |
| 0.1013 | 24.0 | 21120 | 0.0262 | 0.9988 | 1.0166 |
| 0.0998 | 25.0 | 22000 | 0.0388 | 0.9988 | 1.0199 |
| 0.0903 | 26.0 | 22880 | 0.0280 | 0.9988 | 1.0166 |
| 0.088 | 27.0 | 23760 | 0.0492 | 0.9988 | 1.0197 |
| 0.0838 | 28.0 | 24640 | 0.0230 | 0.9988 | 1.0163 |
| 0.079 | 29.0 | 25520 | 0.0282 | 0.9988 | 1.0170 |
| 0.0747 | 30.0 | 26400 | 0.0271 | 0.9988 | 1.0162 |
| 0.0692 | 31.0 | 27280 | 0.0272 | 0.9988 | 1.0167 |
| 0.0699 | 32.0 | 28160 | 0.0427 | 0.9988 | 1.0143 |
| 0.0652 | 33.0 | 29040 | 0.0324 | 0.9988 | 1.0162 |
| 0.0624 | 34.0 | 29920 | 0.0315 | 0.9988 | 1.0163 |
| 0.0588 | 35.0 | 30800 | 0.0549 | 0.9988 | 1.0137 |
| 0.0594 | 36.0 | 31680 | 0.0457 | 0.9988 | 1.0142 |
| 0.0619 | 37.0 | 32560 | 0.0463 | 0.9988 | 1.0144 |
| 0.058 | 38.0 | 33440 | 0.0665 | 0.9988 | 1.0127 |
| 0.059 | 39.0 | 34320 | 0.0595 | 0.9988 | 1.0131 |
| 0.0563 | 39.9551 | 35160 | 0.0581 | 0.9988 | 1.0133 |
### Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0
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