transformers pytorch hubert automatic-speech-recognition generated_from_trainer base_model:rinna/japanese-hubert-base license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: rinna/japanese-hubert-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: jdrt_byclass_rinnna_hubert_asr_3
  results: []
---

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# jdrt_byclass_rinnna_hubert_asr_3

This model is a fine-tuned version of [rinna/japanese-hubert-base](https://huggingface.co/rinna/japanese-hubert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4223
- Wer: 0.4080
- Cer: 0.2885

## 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: 7.5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 260
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 11.2994       | 1.0   | 53   | 6.9048          | 0.9156 | 0.9495 |
| 5.5642        | 2.0   | 106  | 4.4074          | 0.9156 | 0.9495 |
| 4.1184        | 3.0   | 159  | 3.5723          | 0.9156 | 0.9495 |
| 3.2849        | 4.0   | 212  | 2.9362          | 0.9156 | 0.9495 |
| 2.7998        | 5.0   | 265  | 2.6897          | 0.9156 | 0.9495 |
| 2.6983        | 6.0   | 318  | 2.6367          | 0.9156 | 0.9495 |
| 2.4519        | 7.0   | 371  | 2.2030          | 0.9960 | 0.9112 |
| 2.1019        | 8.0   | 424  | 1.8801          | 1.0    | 0.8929 |
| 1.8091        | 9.0   | 477  | 1.5845          | 1.0    | 0.8639 |
| 1.5947        | 10.0  | 530  | 1.3550          | 1.0    | 0.7570 |
| 1.3709        | 11.0  | 583  | 1.2357          | 1.0000 | 0.7344 |
| 1.2377        | 12.0  | 636  | 1.0982          | 1.0000 | 0.6984 |
| 1.1595        | 13.0  | 689  | 0.9865          | 0.9997 | 0.6737 |
| 1.0386        | 14.0  | 742  | 0.9245          | 0.9125 | 0.5754 |
| 0.928         | 15.0  | 795  | 0.8553          | 0.8591 | 0.5117 |
| 0.8691        | 16.0  | 848  | 0.7590          | 0.8435 | 0.4966 |
| 0.7983        | 17.0  | 901  | 0.6782          | 0.5164 | 0.3451 |
| 0.6839        | 18.0  | 954  | 0.5806          | 0.4843 | 0.3323 |
| 0.5901        | 19.0  | 1007 | 0.5280          | 0.4438 | 0.3133 |
| 0.5553        | 20.0  | 1060 | 0.5312          | 0.4434 | 0.3143 |
| 0.5274        | 21.0  | 1113 | 0.5229          | 0.4357 | 0.2939 |
| 0.4843        | 22.0  | 1166 | 0.4674          | 0.4215 | 0.2844 |
| 0.477         | 23.0  | 1219 | 0.4996          | 0.4335 | 0.2984 |
| 0.4624        | 24.0  | 1272 | 0.4762          | 0.4334 | 0.3005 |
| 0.4485        | 25.0  | 1325 | 0.4241          | 0.4286 | 0.3003 |
| 0.4301        | 26.0  | 1378 | 0.4485          | 0.4247 | 0.2923 |
| 0.3953        | 27.0  | 1431 | 0.4292          | 0.4175 | 0.2944 |
| 0.401         | 28.0  | 1484 | 0.4241          | 0.4102 | 0.2868 |
| 0.3833        | 29.0  | 1537 | 0.4053          | 0.3995 | 0.2691 |
| 0.4125        | 30.0  | 1590 | 0.4210          | 0.4013 | 0.2690 |
| 0.3703        | 31.0  | 1643 | 0.4385          | 0.4070 | 0.2744 |
| 0.3441        | 32.0  | 1696 | 0.4126          | 0.4035 | 0.2718 |
| 0.3411        | 33.0  | 1749 | 0.4286          | 0.4125 | 0.2875 |
| 0.3302        | 34.0  | 1802 | 0.4311          | 0.4128 | 0.2943 |
| 0.3422        | 35.0  | 1855 | 0.4350          | 0.4084 | 0.2880 |
| 0.3428        | 36.0  | 1908 | 0.4223          | 0.4080 | 0.2885 |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
