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_1
  results: []
---

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# jdrt_byclass_rinnna_hubert_asr_1

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: 0.3647
- Wer: 0.4190
- Cer: 0.2827

## 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: 0.0001
- 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: 250
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 10.589        | 1.0   | 53   | 5.6588          | 0.9156 | 0.9495 |
| 5.0974        | 2.0   | 106  | 4.0914          | 0.9156 | 0.9495 |
| 3.6701        | 3.0   | 159  | 3.1732          | 0.9156 | 0.9495 |
| 2.9285        | 4.0   | 212  | 2.7238          | 0.9156 | 0.9495 |
| 2.6943        | 5.0   | 265  | 2.6600          | 0.9156 | 0.9495 |
| 2.4567        | 6.0   | 318  | 2.2231          | 0.9960 | 0.9112 |
| 2.1447        | 7.0   | 371  | 1.9716          | 0.9960 | 0.9112 |
| 1.8452        | 8.0   | 424  | 1.5058          | 0.9062 | 0.7431 |
| 1.4358        | 9.0   | 477  | 1.0988          | 0.7370 | 0.5347 |
| 1.1898        | 10.0  | 530  | 0.9512          | 0.6981 | 0.5062 |
| 1.0261        | 11.0  | 583  | 0.8354          | 0.6510 | 0.4779 |
| 0.8371        | 12.0  | 636  | 0.7158          | 0.5560 | 0.3784 |
| 0.7896        | 13.0  | 689  | 0.6381          | 0.5330 | 0.3686 |
| 0.6846        | 14.0  | 742  | 0.5720          | 0.5183 | 0.3555 |
| 0.6357        | 15.0  | 795  | 0.5879          | 0.5030 | 0.3505 |
| 0.5893        | 16.0  | 848  | 0.5501          | 0.4884 | 0.3468 |
| 0.558         | 17.0  | 901  | 0.4291          | 0.4487 | 0.3154 |
| 0.5019        | 18.0  | 954  | 0.4354          | 0.4552 | 0.3064 |
| 0.4784        | 19.0  | 1007 | 0.4199          | 0.4490 | 0.3014 |
| 0.4564        | 20.0  | 1060 | 0.4439          | 0.4508 | 0.3153 |
| 0.4291        | 21.0  | 1113 | 0.4143          | 0.4352 | 0.2845 |
| 0.4144        | 22.0  | 1166 | 0.4415          | 0.4384 | 0.2812 |
| 0.3766        | 23.0  | 1219 | 0.3706          | 0.4264 | 0.2918 |
| 0.3792        | 24.0  | 1272 | 0.3933          | 0.4377 | 0.3015 |
| 0.3759        | 25.0  | 1325 | 0.3708          | 0.4231 | 0.3023 |
| 0.337         | 26.0  | 1378 | 0.3762          | 0.4250 | 0.2942 |
| 0.3282        | 27.0  | 1431 | 0.3595          | 0.4253 | 0.2937 |
| 0.3174        | 28.0  | 1484 | 0.3998          | 0.4269 | 0.2898 |
| 0.3156        | 29.0  | 1537 | 0.4056          | 0.4268 | 0.3093 |
| 0.2921        | 30.0  | 1590 | 0.3694          | 0.4274 | 0.3041 |
| 0.2929        | 31.0  | 1643 | 0.3917          | 0.4228 | 0.2881 |
| 0.2686        | 32.0  | 1696 | 0.3880          | 0.4276 | 0.2969 |
| 0.2776        | 33.0  | 1749 | 0.4038          | 0.4273 | 0.2963 |
| 0.2619        | 34.0  | 1802 | 0.3647          | 0.4190 | 0.2827 |


### Framework versions

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