|
--- |
|
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: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# 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 |
|
|
