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---
library_name: transformers
language:
- zh
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- wft
- whisper
- automatic-speech-recognition
- audio
- speech
- generated_from_trainer
datasets:
- JacobLinCool/common_voice_16_1_zh_TW_clean_preprocessed
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-zh-TW-clean-1
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: JacobLinCool/common_voice_16_1_zh_TW_clean_preprocessed
type: JacobLinCool/common_voice_16_1_zh_TW_clean_preprocessed
metrics:
- type: wer
value: 40.07234726688103
name: Wer
---
<!-- 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. -->
# whisper-large-v3-turbo-zh-TW-clean-1
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the JacobLinCool/common_voice_16_1_zh_TW_clean_preprocessed dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2641
- Wer: 40.0723
- Cer: 11.4336
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|:-------------:|:------:|:----:|:-------:|:---------------:|:-------:|
| No log | 0 | 0 | 22.9952 | 2.8297 | 83.7420 |
| 2.0577 | 0.9987 | 377 | 14.2907 | 0.2666 | 47.9904 |
| 1.9482 | 2.0 | 755 | 14.4991 | 0.2770 | 47.9703 |
| 1.1107 | 2.9987 | 1132 | 15.0615 | 0.2886 | 48.4124 |
| 0.7225 | 4.0 | 1510 | 13.4020 | 0.2736 | 46.2420 |
| 0.5901 | 4.9987 | 1887 | 13.7309 | 0.2759 | 45.2572 |
| 0.4879 | 6.0 | 2265 | 12.9777 | 0.2740 | 44.9759 |
| 0.1874 | 6.9987 | 2642 | 12.7316 | 0.2663 | 44.2524 |
| 0.0544 | 8.0 | 3020 | 12.2295 | 0.2712 | 42.6648 |
| 0.0128 | 8.9987 | 3397 | 11.6068 | 0.2669 | 40.8963 |
| 0.004 | 9.9868 | 3770 | 11.4336 | 0.2641 | 40.0723 |
| 0.004 | 9.9868 | 3770 | 0.2641 | 40.0723 | 11.4336 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.4.0
- Datasets 3.0.2
- Tokenizers 0.20.1 |