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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/mozilla-foundation-common_voice_16_1-zh-TW-preprocessed
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-common_voice_16_1-zh-TW-pissa
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: JacobLinCool/mozilla-foundation-common_voice_16_1-zh-TW-preprocessed
type: JacobLinCool/mozilla-foundation-common_voice_16_1-zh-TW-preprocessed
metrics:
- type: wer
value: 63.665594855305464
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-common_voice_16_1-zh-TW-pissa
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the JacobLinCool/mozilla-foundation-common_voice_16_1-zh-TW-preprocessed dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5133
- Wer: 63.6656
- Cer: 23.5752
## 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 | Validation Loss | Wer | Cer |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
| No log | 0 | 0 | 2.7520 | 77.6125 | 20.7783 |
| 7.6982 | 0.9987 | 377 | 0.8744 | 87.9421 | 41.2804 |
| 5.1677 | 2.0 | 755 | 0.7499 | 82.5965 | 36.6407 |
| 3.3647 | 2.9987 | 1132 | 0.6433 | 76.8087 | 31.6068 |
| 3.4711 | 4.0 | 1510 | 0.6397 | 76.2460 | 30.2862 |
| 1.5694 | 4.9987 | 1887 | 0.5779 | 71.5434 | 27.5471 |
| 0.7951 | 6.0 | 2265 | 0.5664 | 71.3223 | 27.0600 |
| 0.4709 | 6.9987 | 2642 | 0.5492 | 68.8706 | 26.0131 |
| 0.116 | 8.0 | 3020 | 0.5427 | 66.7605 | 24.8104 |
| 0.0512 | 8.9987 | 3397 | 0.5298 | 66.1375 | 24.8632 |
| 0.0273 | 9.9868 | 3770 | 0.5133 | 63.6656 | 23.5752 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.4.0
- Datasets 3.0.2
- Tokenizers 0.20.1 |