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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-2
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: 38.545016077170416
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-2
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: 0.2346
- Wer: 38.5450
- Cer: 10.8963
## 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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- 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 | 2.7503 | 76.5675 | 20.3917 |
| 0.9352 | 0.9987 | 377 | 0.2472 | 47.9301 | 13.6656 |
| 0.73 | 1.9980 | 754 | 0.2502 | 47.0056 | 13.5652 |
| 0.4985 | 2.9974 | 1131 | 0.2559 | 46.2018 | 13.7057 |
| 0.1928 | 3.9993 | 1509 | 0.2595 | 45.9606 | 13.0906 |
| 0.2539 | 4.9987 | 1886 | 0.2522 | 44.7950 | 13.1459 |
| 0.0607 | 5.9980 | 2263 | 0.2422 | 44.7548 | 12.5006 |
| 0.0826 | 6.9974 | 2640 | 0.2488 | 43.8907 | 12.4906 |
| 0.0151 | 7.9993 | 3018 | 0.2403 | 40.2331 | 11.4537 |
| 0.0056 | 8.9987 | 3395 | 0.2390 | 39.8312 | 11.5290 |
| 0.0056 | 9.9927 | 3770 | 0.2346 | 38.5450 | 10.8963 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.4.1+cu124
- Datasets 3.0.2
- Tokenizers 0.20.1 |