metadata
license: apache-2.0
base_model: rinna/japanese-hubert-large
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: hubert-japanese-large-noise-0427
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: default
split: None
args: default
metrics:
- name: Wer
type: wer
value: 0.998
hubert-japanese-large-noise-0427
This model is a fine-tuned version of rinna/japanese-hubert-large on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3383
- Cer: 0.0896
- Wer: 0.998
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 12500.0
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|---|---|---|---|---|---|
| 9.4222 | 1.0 | 2500 | 8.3462 | 0.9998 | 1.0 |
| 3.8795 | 2.0 | 5000 | 3.7791 | 0.7299 | 1.0 |
| 3.6295 | 3.0 | 7500 | 3.5969 | 0.7280 | 1.0 |
| 1.451 | 4.0 | 10000 | 1.0974 | 0.1931 | 1.0 |
| 0.7754 | 5.0 | 12500 | 0.5525 | 0.1595 | 1.0 |
| 0.636 | 6.0 | 15000 | 0.4586 | 0.1605 | 1.0 |
| 0.5528 | 7.0 | 17500 | 0.4240 | 0.1377 | 1.0 |
| 0.5064 | 8.0 | 20000 | 0.3931 | 0.1412 | 1.0 |
| 0.4767 | 9.0 | 22500 | 0.3593 | 0.1403 | 1.0 |
| 0.449 | 10.0 | 25000 | 0.3519 | 0.1112 | 1.0 |
| 0.4261 | 11.0 | 27500 | 0.3578 | 0.1048 | 1.0 |
| 0.4131 | 12.0 | 30000 | 0.3459 | 0.1142 | 1.0 |
| 0.3807 | 13.0 | 32500 | 0.3355 | 0.1072 | 1.0 |
| 0.3759 | 14.0 | 35000 | 0.3380 | 0.0967 | 1.0 |
| 0.3532 | 15.0 | 37500 | 0.3310 | 0.1198 | 1.0 |
| 0.3469 | 16.0 | 40000 | 0.3383 | 0.0927 | 1.0 |
| 0.3297 | 17.0 | 42500 | 0.3363 | 0.0911 | 1.0 |
| 0.3347 | 18.0 | 45000 | 0.3333 | 0.0895 | 0.998 |
| 0.3225 | 19.0 | 47500 | 0.3393 | 0.0944 | 0.998 |
| 0.3199 | 20.0 | 50000 | 0.3341 | 0.0873 | 0.998 |
| 0.3141 | 21.0 | 52500 | 0.3363 | 0.0863 | 0.998 |
| 0.2927 | 22.0 | 55000 | 0.3384 | 0.0889 | 0.998 |
| 0.3051 | 23.0 | 57500 | 0.3389 | 0.0902 | 0.998 |
| 0.3072 | 24.0 | 60000 | 0.3387 | 0.0895 | 0.998 |
| 0.3109 | 25.0 | 62500 | 0.3383 | 0.0896 | 0.998 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.1