metadata
library_name: transformers
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ReVoiceAI-HuBERT-Thai-IPA
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: th
split: None
args: th
metrics:
- name: Wer
type: wer
value: 0.2411430758435925
ReVoiceAI-HuBERT-Thai-IPA
This model is a fine-tuned version of facebook/hubert-base-ls960 on the common_voice_17_0 (mapped to phonemic IPA) dataset. It achieves the following results on the evaluation set:
- Loss: -1.0097
- Wer: 0.2411
- Cer: 0.0791
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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| -0.6917 | 1.0 | 936 | -0.7912 | 0.4519 | 0.1585 |
| -0.5931 | 2.0 | 1872 | -0.8088 | 0.4398 | 0.1575 |
| -0.5726 | 3.0 | 2808 | -0.8250 | 0.4368 | 0.1507 |
| -0.5981 | 4.0 | 3744 | -0.8131 | 0.4270 | 0.1466 |
| -0.5875 | 5.0 | 4680 | -0.8349 | 0.4235 | 0.1435 |
| -0.6103 | 6.0 | 5616 | -0.8398 | 0.4353 | 0.1510 |
| -0.628 | 7.0 | 6552 | -0.8283 | 0.4069 | 0.1419 |
| -0.6334 | 8.0 | 7488 | -0.8420 | 0.3986 | 0.1353 |
| -0.6452 | 9.0 | 8424 | -0.8667 | 0.3889 | 0.1317 |
| -0.6724 | 10.0 | 9360 | -0.8883 | 0.3879 | 0.1341 |
| -0.6735 | 11.0 | 10296 | -0.8766 | 0.3996 | 0.1353 |
| -0.6745 | 12.0 | 11232 | -0.8851 | 0.3597 | 0.1231 |
| -0.7151 | 13.0 | 12168 | -0.9114 | 0.3450 | 0.1179 |
| -0.7099 | 14.0 | 13104 | -0.9199 | 0.3253 | 0.1107 |
| -0.736 | 15.0 | 14040 | -0.9214 | 0.3226 | 0.1083 |
| -0.7644 | 16.0 | 14976 | -0.9648 | 0.3106 | 0.1042 |
| -0.7684 | 17.0 | 15912 | -0.9583 | 0.3159 | 0.1060 |
| -0.7815 | 18.0 | 16848 | -0.9573 | 0.2921 | 0.0983 |
| -0.8026 | 19.0 | 17784 | -0.9406 | 0.3260 | 0.1073 |
| -0.8239 | 20.0 | 18720 | -0.9867 | 0.2845 | 0.0957 |
| -0.8248 | 21.0 | 19656 | -0.9921 | 0.2723 | 0.0903 |
| -0.8463 | 22.0 | 20592 | -1.0006 | 0.2632 | 0.0882 |
| -0.8622 | 23.0 | 21528 | -1.0012 | 0.2564 | 0.0849 |
| -0.8485 | 24.0 | 22464 | -1.0012 | 0.2558 | 0.0837 |
| -0.856 | 25.0 | 23400 | -1.0023 | 0.2570 | 0.0839 |
| -0.8768 | 26.0 | 24336 | -0.9986 | 0.2489 | 0.0820 |
| -0.8987 | 27.0 | 25272 | -1.0149 | 0.2416 | 0.0793 |
| -0.8845 | 28.0 | 26208 | -1.0041 | 0.2453 | 0.0802 |
| -0.8812 | 29.0 | 27144 | -1.0108 | 0.2409 | 0.0791 |
| -0.8906 | 30.0 | 28080 | -1.0097 | 0.2411 | 0.0791 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1
- Datasets 3.6.0
- Tokenizers 0.21.0