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---
language:
- zh
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Traditional Chinese
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 zh-TW
type: mozilla-foundation/common_voice_11_0
config: zh-TW
split: test
args: zh-TW
metrics:
- name: Wer
type: wer
value: 32.594792142530835
---
<!-- 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 Small Traditional Chinese
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 zh-TW dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3250
- Wer: 32.5948
## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 800
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3465 | 1.05 | 200 | 0.3499 | 41.9324 |
| 0.2137 | 2.1 | 400 | 0.2953 | 36.2951 |
| 0.1255 | 4.01 | 600 | 0.2927 | 33.7232 |
| 0.0509 | 5.06 | 800 | 0.3149 | 34.0566 |
| 0.0164 | 6.11 | 1000 | 0.3250 | 32.5948 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|