---
library_name: transformers
license: apache-2.0
base_model: rinna/japanese-hubert-base
tags:
- automatic-speech-recognition
- original_kakeiken_W_elevator_hall
- generated_from_trainer
metrics:
- wer
model-index:
- name: Hubert-kakeiken-W-elevator_hall
  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-elevator_hall

This model is a fine-tuned version of [rinna/japanese-hubert-base](https://huggingface.co./rinna/japanese-hubert-base) on the ORIGINAL_KAKEIKEN_W_ELEVATOR_HALL - JA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0253
- Wer: 0.9988
- Cer: 1.0162

## 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    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
| 53.9873       | 1.0     | 820   | 19.7137         | 1.0    | 1.1284 |
| 16.2788       | 2.0     | 1640  | 12.8321         | 1.0    | 1.1284 |
| 11.6832       | 3.0     | 2460  | 5.6187          | 1.0    | 1.1284 |
| 4.3059        | 4.0     | 3280  | 3.3938          | 1.0    | 1.1284 |
| 3.1294        | 5.0     | 4100  | 2.8854          | 1.0    | 1.1284 |
| 2.6448        | 6.0     | 4920  | 1.4073          | 1.0    | 1.1019 |
| 1.022         | 7.0     | 5740  | 0.6323          | 1.0    | 1.0336 |
| 0.4449        | 8.0     | 6560  | 0.3110          | 0.9988 | 1.0403 |
| 0.305         | 9.0     | 7380  | 0.2348          | 0.9991 | 1.0485 |
| 0.1895        | 10.0    | 8200  | 0.1109          | 0.9988 | 1.0230 |
| 0.1437        | 11.0    | 9020  | 0.0931          | 0.9990 | 1.0221 |
| 0.1258        | 12.0    | 9840  | 0.0828          | 0.9988 | 1.0258 |
| 0.1175        | 13.0    | 10660 | 0.0814          | 0.9991 | 1.0232 |
| 0.1083        | 14.0    | 11480 | 0.0415          | 0.9988 | 1.0194 |
| 0.0974        | 15.0    | 12300 | 0.0653          | 0.9990 | 1.0239 |
| 0.0967        | 16.0    | 13120 | 0.0495          | 0.9991 | 1.0200 |
| 0.087         | 17.0    | 13940 | 0.0601          | 0.9990 | 1.0224 |
| 0.0798        | 18.0    | 14760 | 0.0544          | 0.9990 | 1.0218 |
| 0.0719        | 19.0    | 15580 | 0.0426          | 0.9990 | 1.0191 |
| 0.0731        | 20.0    | 16400 | 0.0587          | 0.9991 | 1.0208 |
| 0.0693        | 21.0    | 17220 | 0.0603          | 0.9988 | 1.0222 |
| 0.0614        | 22.0    | 18040 | 0.0361          | 0.9988 | 1.0191 |
| 0.0582        | 23.0    | 18860 | 0.0332          | 0.9988 | 1.0173 |
| 0.0535        | 24.0    | 19680 | 0.0347          | 0.9988 | 1.0172 |
| 0.0467        | 25.0    | 20500 | 0.0334          | 0.9988 | 1.0180 |
| 0.0456        | 26.0    | 21320 | 0.0283          | 0.9988 | 1.0164 |
| 0.0389        | 27.0    | 22140 | 0.0361          | 0.9988 | 1.0172 |
| 0.04          | 28.0    | 22960 | 0.0258          | 0.9988 | 1.0167 |
| 0.0348        | 29.0    | 23780 | 0.0328          | 0.9990 | 1.0176 |
| 0.0343        | 30.0    | 24600 | 0.0276          | 0.9988 | 1.0162 |
| 0.0323        | 31.0    | 25420 | 0.0297          | 0.9988 | 1.0165 |
| 0.0283        | 32.0    | 26240 | 0.0291          | 0.9988 | 1.0165 |
| 0.0275        | 33.0    | 27060 | 0.0252          | 0.9988 | 1.0161 |
| 0.0256        | 34.0    | 27880 | 0.0245          | 0.9988 | 1.0164 |
| 0.0241        | 35.0    | 28700 | 0.0240          | 0.9988 | 1.0159 |
| 0.0237        | 36.0    | 29520 | 0.0278          | 0.9988 | 1.0166 |
| 0.0238        | 37.0    | 30340 | 0.0275          | 0.9988 | 1.0163 |
| 0.022         | 38.0    | 31160 | 0.0247          | 0.9988 | 1.0163 |
| 0.0184        | 39.0    | 31980 | 0.0262          | 0.9988 | 1.0163 |
| 0.0199        | 39.9518 | 32760 | 0.0244          | 0.9988 | 1.0160 |


### Framework versions

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