metadata
license: apache-2.0
base_model: rinna/japanese-hubert-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: jdrt_byclass_rinnna_hubert_asr_2
results: []
jdrt_byclass_rinnna_hubert_asr_2
This model is a fine-tuned version of rinna/japanese-hubert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4574
- Wer: 0.4461
- Cer: 0.3253
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: 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 |
|---|---|---|---|---|---|
| 11.8822 | 1.0 | 53 | 8.0828 | 0.9838 | 0.9911 |
| 6.3754 | 2.0 | 106 | 4.6774 | 0.9838 | 0.9911 |
| 4.5264 | 3.0 | 159 | 3.9963 | 0.9838 | 0.9911 |
| 3.7867 | 4.0 | 212 | 3.3575 | 0.9838 | 0.9911 |
| 3.2022 | 5.0 | 265 | 2.9007 | 0.9838 | 0.9911 |
| 2.8134 | 6.0 | 318 | 2.7079 | 0.9838 | 0.9911 |
| 2.708 | 7.0 | 371 | 2.6779 | 0.9838 | 0.9911 |
| 2.6923 | 8.0 | 424 | 2.6719 | 0.9838 | 0.9911 |
| 2.6555 | 9.0 | 477 | 2.4997 | 0.9838 | 0.9911 |
| 2.3308 | 10.0 | 530 | 2.1709 | 0.9960 | 0.9522 |
| 2.1951 | 11.0 | 583 | 2.0579 | 0.9960 | 0.9522 |
| 2.0032 | 12.0 | 636 | 1.8255 | 0.9989 | 0.9302 |
| 1.8394 | 13.0 | 689 | 1.6870 | 0.9999 | 0.9021 |
| 1.6562 | 14.0 | 742 | 1.4793 | 0.9999 | 0.8139 |
| 1.5057 | 15.0 | 795 | 1.2942 | 0.9997 | 0.7813 |
| 1.4022 | 16.0 | 848 | 1.2146 | 0.9997 | 0.7594 |
| 1.2945 | 17.0 | 901 | 1.1512 | 0.9941 | 0.7395 |
| 1.2062 | 18.0 | 954 | 1.0732 | 0.9844 | 0.6726 |
| 1.1396 | 19.0 | 1007 | 1.0457 | 0.9694 | 0.6559 |
| 1.0419 | 20.0 | 1060 | 0.8567 | 0.5929 | 0.4214 |
| 0.8799 | 21.0 | 1113 | 0.7172 | 0.5273 | 0.3951 |
| 0.8249 | 22.0 | 1166 | 0.6980 | 0.5204 | 0.4048 |
| 0.7649 | 23.0 | 1219 | 0.6157 | 0.4923 | 0.3737 |
| 0.7401 | 24.0 | 1272 | 0.6171 | 0.4992 | 0.3722 |
| 0.7074 | 25.0 | 1325 | 0.5948 | 0.4835 | 0.3669 |
| 0.6543 | 26.0 | 1378 | 0.5520 | 0.4759 | 0.3537 |
| 0.6164 | 27.0 | 1431 | 0.5512 | 0.4745 | 0.3467 |
| 0.5758 | 28.0 | 1484 | 0.5286 | 0.4677 | 0.3416 |
| 0.5648 | 29.0 | 1537 | 0.5099 | 0.4644 | 0.3447 |
| 0.578 | 30.0 | 1590 | 0.5262 | 0.4701 | 0.3530 |
| 0.5343 | 31.0 | 1643 | 0.5025 | 0.4621 | 0.3463 |
| 0.5236 | 32.0 | 1696 | 0.4927 | 0.4588 | 0.3411 |
| 0.5256 | 33.0 | 1749 | 0.4971 | 0.4614 | 0.3434 |
| 0.5309 | 34.0 | 1802 | 0.4882 | 0.4553 | 0.3400 |
| 0.4938 | 35.0 | 1855 | 0.4663 | 0.4497 | 0.3309 |
| 0.4874 | 36.0 | 1908 | 0.4734 | 0.4508 | 0.3316 |
| 0.4519 | 37.0 | 1961 | 0.4642 | 0.4483 | 0.3289 |
| 0.5137 | 38.0 | 2014 | 0.4655 | 0.4490 | 0.3303 |
| 0.4832 | 39.0 | 2067 | 0.4613 | 0.4474 | 0.3282 |
| 0.4581 | 40.0 | 2120 | 0.4565 | 0.4450 | 0.3236 |
| 0.4542 | 41.0 | 2173 | 0.4550 | 0.4461 | 0.3262 |
| 0.4478 | 42.0 | 2226 | 0.4548 | 0.4442 | 0.3247 |
| 0.448 | 43.0 | 2279 | 0.4523 | 0.4450 | 0.3238 |
| 0.4468 | 44.0 | 2332 | 0.4560 | 0.4455 | 0.3224 |
| 0.4681 | 45.0 | 2385 | 0.4599 | 0.4468 | 0.3253 |
| 0.455 | 46.0 | 2438 | 0.4589 | 0.4472 | 0.3246 |
| 0.4479 | 47.0 | 2491 | 0.4583 | 0.4465 | 0.3245 |
| 0.4533 | 48.0 | 2544 | 0.4582 | 0.4469 | 0.3253 |
| 0.4486 | 49.0 | 2597 | 0.4575 | 0.4462 | 0.3253 |
| 0.4466 | 50.0 | 2650 | 0.4574 | 0.4461 | 0.3253 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3