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---
library_name: transformers
language:
- yue
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
- mozilla-foundation/common_voice_16_1
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Small Canontese X v3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.0
type: mozilla-foundation/common_voice_17_0
config: yue
split: None
args: 'config: zh-HK, split: test'
metrics:
- name: Wer
type: wer
value: 55.631920580374185
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.1
type: mozilla-foundation/common_voice_16_1
metrics:
- name: Wer
type: wer
value: 55.631920580374185
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_16_0
metrics:
- name: Wer
type: wer
value: 55.631920580374185
---
<!-- 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 Canontese X v3
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.0, the Common Voice 16.1 and the Common Voice 17.0 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.2650
- Wer: 55.6319
## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0845 | 0.7087 | 1000 | 0.2773 | 61.5120 |
| 0.0285 | 1.4174 | 2000 | 0.2697 | 56.7010 |
| 0.0102 | 2.1262 | 3000 | 0.2650 | 55.6319 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
|