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# hubert-rinna-jdrt-RTSPsplit-0205-4

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: 0.0143
- Wer: 0.1611
- Cer: 0.0491

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 14.3954       | 1.0   | 60   | 12.0778         | 0.9859 | 0.9957 |
| 6.8176        | 2.0   | 120  | 6.1526          | 0.9859 | 0.9957 |
| 5.1951        | 3.0   | 180  | 4.9224          | 0.9859 | 0.9957 |
| 4.0471        | 4.0   | 240  | 3.8527          | 0.9859 | 0.9957 |
| 3.3262        | 5.0   | 300  | 3.1827          | 0.9859 | 0.9957 |
| 2.7825        | 6.0   | 360  | 2.7018          | 0.9859 | 0.9957 |
| 2.0715        | 7.0   | 420  | 1.9557          | 1.0    | 0.8553 |
| 1.532         | 8.0   | 480  | 1.2990          | 1.0    | 0.5628 |
| 1.1659        | 9.0   | 540  | 1.1185          | 1.0    | 0.5728 |
| 1.0958        | 10.0  | 600  | 1.0125          | 1.0    | 0.5032 |
| 0.9227        | 11.0  | 660  | 0.7811          | 0.7987 | 0.4499 |
| 0.7595        | 12.0  | 720  | 0.7222          | 0.7975 | 0.4485 |
| 0.7473        | 13.0  | 780  | 0.6966          | 0.8121 | 0.4961 |
| 0.6781        | 14.0  | 840  | 0.6520          | 0.7983 | 0.4525 |
| 0.6756        | 15.0  | 900  | 0.6458          | 0.7793 | 0.3855 |
| 0.6267        | 16.0  | 960  | 0.6690          | 0.7983 | 0.4226 |
| 0.7067        | 17.0  | 1020 | 0.5960          | 0.7633 | 0.3807 |
| 1.0034        | 18.0  | 1080 | 0.5118          | 0.7440 | 0.3660 |
| 0.5187        | 19.0  | 1140 | 0.4738          | 0.6677 | 0.2861 |
| 0.4873        | 20.0  | 1200 | 0.4277          | 0.6487 | 0.2751 |
| 0.4776        | 21.0  | 1260 | 0.3999          | 0.5828 | 0.2317 |
| 0.5306        | 22.0  | 1320 | 0.3716          | 0.5683 | 0.2189 |
| 0.3851        | 23.0  | 1380 | 0.3221          | 0.5244 | 0.1889 |
| 0.3404        | 24.0  | 1440 | 0.2676          | 0.4269 | 0.1472 |
| 0.2967        | 25.0  | 1500 | 0.2283          | 0.3971 | 0.1372 |
| 0.2753        | 26.0  | 1560 | 0.1950          | 0.3591 | 0.1198 |
| 0.2362        | 27.0  | 1620 | 0.1621          | 0.3256 | 0.1067 |
| 0.2201        | 28.0  | 1680 | 0.1502          | 0.3197 | 0.1056 |
| 0.1827        | 29.0  | 1740 | 0.1164          | 0.2750 | 0.0871 |
| 0.1767        | 30.0  | 1800 | 0.1204          | 0.2780 | 0.0880 |
| 0.1612        | 31.0  | 1860 | 0.0946          | 0.2419 | 0.0752 |
| 0.1615        | 32.0  | 1920 | 0.0831          | 0.2471 | 0.0760 |
| 0.1414        | 33.0  | 1980 | 0.0665          | 0.2222 | 0.0681 |
| 0.1175        | 34.0  | 2040 | 0.0594          | 0.2129 | 0.0651 |
| 0.1523        | 35.0  | 2100 | 0.0607          | 0.2151 | 0.0652 |
| 0.0955        | 36.0  | 2160 | 0.0490          | 0.2092 | 0.0642 |
| 0.0927        | 37.0  | 2220 | 0.0420          | 0.1935 | 0.0591 |
| 0.077         | 38.0  | 2280 | 0.0478          | 0.2025 | 0.0617 |
| 0.0688        | 39.0  | 2340 | 0.0344          | 0.1894 | 0.0577 |
| 0.1159        | 40.0  | 2400 | 0.0333          | 0.1887 | 0.0573 |
| 0.0697        | 41.0  | 2460 | 0.0319          | 0.1850 | 0.0562 |
| 0.0596        | 42.0  | 2520 | 0.0325          | 0.1857 | 0.0566 |
| 0.0503        | 43.0  | 2580 | 0.0226          | 0.1723 | 0.0524 |
| 0.0598        | 44.0  | 2640 | 0.0214          | 0.1712 | 0.0523 |
| 0.0871        | 45.0  | 2700 | 0.0192          | 0.1727 | 0.0525 |
| 0.0433        | 46.0  | 2760 | 0.0182          | 0.1682 | 0.0512 |
| 0.0455        | 47.0  | 2820 | 0.0165          | 0.1641 | 0.05   |
| 0.045         | 48.0  | 2880 | 0.0149          | 0.1626 | 0.0495 |
| 0.0454        | 49.0  | 2940 | 0.0144          | 0.1634 | 0.0498 |
| 0.0347        | 50.0  | 3000 | 0.0143          | 0.1611 | 0.0491 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "rinna/japanese-hubert-base", "model-index": [{"name": "hubert-rinna-jdrt-RTSPsplit-0205-4", "results": []}]}
transformers safetensors hubert automatic-speech-recognition generated_from_trainer base_model:rinna/japanese-hubert-base license:apache-2.0 endpoints_compatible region:us