--- 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: [] --- # 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