metadata
library_name: transformers
language:
- ja
license: apache-2.0
base_model: rinna/japanese-hubert-base
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_13_0
- generated_from_trainer
metrics:
- wer
model-index:
- name: Hubert-common_voice-phoneme-debug-warmup500
results: []
Hubert-common_voice-phoneme-debug-warmup500
This model is a fine-tuned version of rinna/japanese-hubert-base on the MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - JA dataset. It achieves the following results on the evaluation set:
- Loss: 2.9679
- Wer: 1.0
- Cer: 0.9851
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 500
- num_epochs: 30.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| No log | 0.7092 | 100 | 4.5669 | 1.0 | 0.9851 |
| No log | 1.4184 | 200 | 3.0119 | 1.0 | 0.9851 |
| No log | 2.1277 | 300 | 2.9840 | 1.0 | 0.9851 |
| No log | 2.8369 | 400 | 2.9764 | 1.0 | 0.9851 |
| 3.973 | 3.5461 | 500 | 2.9796 | 1.0 | 0.9851 |
| 3.973 | 4.2553 | 600 | 2.9758 | 1.0 | 0.9851 |
| 3.973 | 4.9645 | 700 | 2.9691 | 1.0 | 0.9851 |
| 3.973 | 5.6738 | 800 | 2.9858 | 1.0 | 0.9850 |
| 3.973 | 6.3830 | 900 | 2.9692 | 1.0 | 0.9851 |
| 2.9654 | 7.0922 | 1000 | 2.9895 | 1.0 | 0.9850 |
| 2.9654 | 7.8014 | 1100 | 2.9725 | 1.0 | 0.9850 |
| 2.9654 | 8.5106 | 1200 | 2.9713 | 1.0 | 0.9850 |
| 2.9654 | 9.2199 | 1300 | 2.9758 | 1.0 | 0.9851 |
| 2.9654 | 9.9291 | 1400 | 2.9784 | 1.0 | 0.9850 |
| 2.9643 | 10.6383 | 1500 | 2.9687 | 1.0 | 0.9851 |
| 2.9643 | 11.3475 | 1600 | 2.9779 | 1.0 | 0.9851 |
| 2.9643 | 12.0567 | 1700 | 2.9679 | 1.0 | 0.9850 |
| 2.9643 | 12.7660 | 1800 | 2.9769 | 1.0 | 0.9851 |
| 2.9643 | 13.4752 | 1900 | 2.9718 | 1.0 | 0.9851 |
| 2.9631 | 14.1844 | 2000 | 2.9686 | 1.0 | 0.9851 |
| 2.9631 | 14.8936 | 2100 | 2.9706 | 1.0 | 0.9850 |
| 2.9631 | 15.6028 | 2200 | 2.9791 | 1.0 | 0.9851 |
| 2.9631 | 16.3121 | 2300 | 2.9731 | 1.0 | 0.9851 |
| 2.9631 | 17.0213 | 2400 | 2.9722 | 1.0 | 0.9850 |
| 2.9627 | 17.7305 | 2500 | 2.9723 | 1.0 | 0.9851 |
| 2.9627 | 18.4397 | 2600 | 2.9689 | 1.0 | 0.9851 |
| 2.9627 | 19.1489 | 2700 | 2.9747 | 1.0 | 0.9851 |
| 2.9627 | 19.8582 | 2800 | 2.9801 | 1.0 | 0.9851 |
| 2.9627 | 20.5674 | 2900 | 2.9740 | 1.0 | 0.9851 |
| 2.9622 | 21.2766 | 3000 | 2.9736 | 1.0 | 0.9850 |
| 2.9622 | 21.9858 | 3100 | 2.9719 | 1.0 | 0.9851 |
| 2.9622 | 22.6950 | 3200 | 2.9710 | 1.0 | 0.9850 |
| 2.9622 | 23.4043 | 3300 | 2.9714 | 1.0 | 0.9850 |
| 2.9622 | 24.1135 | 3400 | 2.9701 | 1.0 | 0.9851 |
| 2.9609 | 24.8227 | 3500 | 2.9695 | 1.0 | 0.9851 |
| 2.9609 | 25.5319 | 3600 | 2.9669 | 1.0 | 0.9850 |
| 2.9609 | 26.2411 | 3700 | 2.9774 | 1.0 | 0.9851 |
| 2.9609 | 26.9504 | 3800 | 2.9712 | 1.0 | 0.9851 |
| 2.9609 | 27.6596 | 3900 | 2.9701 | 1.0 | 0.9851 |
| 2.962 | 28.3688 | 4000 | 2.9689 | 1.0 | 0.9851 |
| 2.962 | 29.0780 | 4100 | 2.9738 | 1.0 | 0.9850 |
| 2.962 | 29.7872 | 4200 | 2.9678 | 1.0 | 0.9851 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3