---
library_name: transformers
license: apache-2.0
base_model: rinna/japanese-hubert-base
tags:
- automatic-speech-recognition
- original_kakeiken_W_lounge
- generated_from_trainer
metrics:
- wer
model-index:
- name: Hubert-kakeiken-W-lounge
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Hubert-kakeiken-W-lounge

This model is a fine-tuned version of [rinna/japanese-hubert-base](https://huggingface.co/rinna/japanese-hubert-base) on the ORIGINAL_KAKEIKEN_W_LOUNGE - JA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0115
- Wer: 0.9988
- Cer: 1.0143

## 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    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
| 40.3051       | 1.0     | 820   | 14.9753         | 1.0    | 1.1284 |
| 12.3062       | 2.0     | 1640  | 9.9534          | 1.0    | 1.1284 |
| 9.0113        | 3.0     | 2460  | 4.8377          | 1.0    | 1.1284 |
| 3.9478        | 4.0     | 3280  | 3.2016          | 1.0    | 1.1284 |
| 2.7396        | 5.0     | 4100  | 2.4831          | 1.0    | 1.1284 |
| 2.2509        | 6.0     | 4920  | 0.9198          | 0.9999 | 1.1054 |
| 0.6886        | 7.0     | 5740  | 0.3222          | 0.9991 | 1.0273 |
| 0.318         | 8.0     | 6560  | 0.1601          | 0.9991 | 1.0191 |
| 0.255         | 9.0     | 7380  | 0.0902          | 0.9988 | 1.0176 |
| 0.1835        | 10.0    | 8200  | 0.0716          | 0.9991 | 1.0197 |
| 0.16          | 11.0    | 9020  | 0.0492          | 0.9988 | 1.0175 |
| 0.1444        | 12.0    | 9840  | 0.0344          | 0.9990 | 1.0162 |
| 0.1307        | 13.0    | 10660 | 0.0388          | 0.9988 | 1.0176 |
| 0.1346        | 14.0    | 11480 | 0.0277          | 0.9990 | 1.0167 |
| 0.1257        | 15.0    | 12300 | 0.0267          | 0.9988 | 1.0164 |
| 0.1157        | 16.0    | 13120 | 0.0276          | 0.9990 | 1.0166 |
| 0.1104        | 17.0    | 13940 | 0.0341          | 0.9988 | 1.0172 |
| 0.1086        | 18.0    | 14760 | 0.0236          | 0.9988 | 1.0167 |
| 0.1072        | 19.0    | 15580 | 0.0306          | 0.9988 | 1.0175 |
| 0.128         | 20.0    | 16400 | 0.0241          | 0.9988 | 1.0160 |
| 0.0987        | 21.0    | 17220 | 0.0242          | 0.9988 | 1.0165 |
| 0.1031        | 22.0    | 18040 | 0.0229          | 0.9990 | 1.0159 |
| 0.0903        | 23.0    | 18860 | 0.0261          | 0.9988 | 1.0162 |
| 0.0895        | 24.0    | 19680 | 0.0322          | 0.9988 | 1.0177 |
| 0.0835        | 25.0    | 20500 | 0.0188          | 0.9988 | 1.0152 |
| 0.0744        | 26.0    | 21320 | 0.0179          | 0.9988 | 1.0149 |
| 0.0728        | 27.0    | 22140 | 0.0107          | 0.9988 | 1.0145 |
| 0.0704        | 28.0    | 22960 | 0.0161          | 0.9988 | 1.0149 |
| 0.068         | 29.0    | 23780 | 0.0140          | 0.9988 | 1.0150 |
| 0.0635        | 30.0    | 24600 | 0.0179          | 0.9988 | 1.0148 |
| 0.0606        | 31.0    | 25420 | 0.0170          | 0.9988 | 1.0146 |
| 0.0549        | 32.0    | 26240 | 0.0127          | 0.9988 | 1.0146 |
| 0.0557        | 33.0    | 27060 | 0.0112          | 0.9988 | 1.0146 |
| 0.0525        | 34.0    | 27880 | 0.0140          | 0.9988 | 1.0146 |
| 0.0478        | 35.0    | 28700 | 0.0125          | 0.9988 | 1.0146 |
| 0.0475        | 36.0    | 29520 | 0.0124          | 0.9988 | 1.0146 |
| 0.0455        | 37.0    | 30340 | 0.0114          | 0.9988 | 1.0142 |
| 0.0444        | 38.0    | 31160 | 0.0118          | 0.9988 | 1.0142 |
| 0.0476        | 39.0    | 31980 | 0.0119          | 0.9988 | 1.0142 |
| 0.0464        | 39.9518 | 32760 | 0.0115          | 0.9988 | 1.0143 |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0