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
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: Hubert-common_voice-ja-demo-phonemes-cosine-3e-5
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - JA
type: common_voice_13_0
config: ja
split: test
args: 'Config: ja, Training split: train+validation, Eval split: test'
metrics:
- name: Wer
type: wer
value: 1
Hubert-common_voice-ja-demo-phonemes-cosine-3e-5
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: inf
- Wer: 1.0
- Cer: 0.2359
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: 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: 12500
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| No log | 0.2660 | 100 | inf | 1.8204 | 4.9067 |
| No log | 0.5319 | 200 | inf | 1.5926 | 4.6323 |
| No log | 0.7979 | 300 | inf | 1.1770 | 1.9637 |
| No log | 1.0638 | 400 | inf | 1.0 | 0.9817 |
| 14.493 | 1.3298 | 500 | inf | 1.0 | 0.9817 |
| 14.493 | 1.5957 | 600 | inf | 1.0 | 0.9817 |
| 14.493 | 1.8617 | 700 | inf | 1.0 | 0.9817 |
| 14.493 | 2.1277 | 800 | inf | 1.0 | 0.9817 |
| 14.493 | 2.3936 | 900 | inf | 1.0 | 0.9817 |
| 6.5744 | 2.6596 | 1000 | 6.8080 | 1.0 | 0.9817 |
| 6.5744 | 2.9255 | 1100 | 6.5972 | 1.0 | 0.9817 |
| 6.5744 | 3.1915 | 1200 | inf | 1.0 | 0.9817 |
| 6.5744 | 3.4574 | 1300 | inf | 1.0 | 0.9817 |
| 6.5744 | 3.7234 | 1400 | inf | 1.0 | 0.9817 |
| 5.5193 | 3.9894 | 1500 | inf | 1.0 | 0.9817 |
| 5.5193 | 4.2553 | 1600 | inf | 1.0 | 0.9817 |
| 5.5193 | 4.5213 | 1700 | inf | 1.0 | 0.9817 |
| 5.5193 | 4.7872 | 1800 | inf | 1.0 | 0.9817 |
| 5.5193 | 5.0532 | 1900 | inf | 1.0 | 0.9817 |
| 4.5578 | 5.3191 | 2000 | inf | 1.0 | 0.9817 |
| 4.5578 | 5.5851 | 2100 | inf | 1.0 | 0.9817 |
| 4.5578 | 5.8511 | 2200 | inf | 1.0 | 0.9817 |
| 4.5578 | 6.1170 | 2300 | inf | 1.0 | 0.9817 |
| 4.5578 | 6.3830 | 2400 | inf | 1.0 | 0.9817 |
| 3.6943 | 6.6489 | 2500 | inf | 1.0 | 0.9817 |
| 3.6943 | 6.9149 | 2600 | inf | 1.0 | 0.9817 |
| 3.6943 | 7.1809 | 2700 | inf | 1.0 | 0.9817 |
| 3.6943 | 7.4468 | 2800 | inf | 1.0 | 0.9817 |
| 3.6943 | 7.7128 | 2900 | 3.1572 | 1.0 | 0.9817 |
| 3.1932 | 7.9787 | 3000 | inf | 1.0 | 0.9817 |
| 3.1932 | 8.2447 | 3100 | inf | 1.0 | 0.9817 |
| 3.1932 | 8.5106 | 3200 | inf | 1.0 | 0.9817 |
| 3.1932 | 8.7766 | 3300 | inf | 1.0 | 0.9817 |
| 3.1932 | 9.0426 | 3400 | inf | 1.0 | 0.9817 |
| 3.0309 | 9.3085 | 3500 | inf | 1.0 | 0.9817 |
| 3.0309 | 9.5745 | 3600 | inf | 1.0 | 0.9817 |
| 3.0309 | 9.8404 | 3700 | inf | 1.0 | 0.9817 |
| 3.0309 | 10.1064 | 3800 | inf | 1.0 | 0.9817 |
| 3.0309 | 10.3723 | 3900 | inf | 1.0 | 0.9817 |
| 2.9704 | 10.6383 | 4000 | inf | 1.0 | 0.9817 |
| 2.9704 | 10.9043 | 4100 | inf | 1.0 | 0.9817 |
| 2.9704 | 11.1702 | 4200 | inf | 1.0 | 0.9049 |
| 2.9704 | 11.4362 | 4300 | inf | 1.0 | 0.7254 |
| 2.9704 | 11.7021 | 4400 | inf | 1.0 | 0.4365 |
| 2.2767 | 11.9681 | 4500 | 1.5675 | 1.0 | 0.3732 |
| 2.2767 | 12.2340 | 4600 | inf | 1.0 | 0.3455 |
| 2.2767 | 12.5 | 4700 | inf | 1.0 | 0.3277 |
| 2.2767 | 12.7660 | 4800 | inf | 1.0 | 0.3053 |
| 2.2767 | 13.0319 | 4900 | inf | 1.0 | 0.2935 |
| 1.2873 | 13.2979 | 5000 | inf | 1.0 | 0.2784 |
| 1.2873 | 13.5638 | 5100 | inf | 1.0 | 0.2684 |
| 1.2873 | 13.8298 | 5200 | inf | 1.0 | 0.2678 |
| 1.2873 | 14.0957 | 5300 | inf | 1.0 | 0.2616 |
| 1.2873 | 14.3617 | 5400 | 0.8214 | 1.0 | 0.2608 |
| 0.9318 | 14.6277 | 5500 | inf | 1.0 | 0.2564 |
| 0.9318 | 14.8936 | 5600 | inf | 1.0 | 0.2544 |
| 0.9318 | 15.1596 | 5700 | inf | 1.0 | 0.2525 |
| 0.9318 | 15.4255 | 5800 | inf | 1.0 | 0.2510 |
| 0.9318 | 15.6915 | 5900 | inf | 1.0 | 0.2527 |
| 0.754 | 15.9574 | 6000 | inf | 1.0 | 0.2499 |
| 0.754 | 16.2234 | 6100 | 0.6672 | 1.0 | 0.2485 |
| 0.754 | 16.4894 | 6200 | inf | 1.0 | 0.2464 |
| 0.754 | 16.7553 | 6300 | inf | 1.0 | 0.2467 |
| 0.754 | 17.0213 | 6400 | inf | 1.0 | 0.2411 |
| 0.6421 | 17.2872 | 6500 | inf | 1.0 | 0.2411 |
| 0.6421 | 17.5532 | 6600 | inf | 1.0 | 0.2418 |
| 0.6421 | 17.8191 | 6700 | inf | 1.0 | 0.2386 |
| 0.6421 | 18.0851 | 6800 | inf | 0.9996 | 0.2387 |
| 0.6421 | 18.3511 | 6900 | inf | 1.0 | 0.2381 |
| 0.568 | 18.6170 | 7000 | inf | 1.0 | 0.2391 |
| 0.568 | 18.8830 | 7100 | inf | 1.0 | 0.2370 |
| 0.568 | 19.1489 | 7200 | inf | 1.0 | 0.2344 |
| 0.568 | 19.4149 | 7300 | inf | 1.0 | 0.2364 |
| 0.568 | 19.6809 | 7400 | inf | 1.0 | 0.2347 |
| 0.5259 | 19.9468 | 7500 | inf | 1.0 | 0.2334 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3