---
library_name: transformers
language:
- yue
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_15_0
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Small Canontese X v2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.1
      type: mozilla-foundation/common_voice_15_0
      config: zh-HK
      split: None
      args: 'config: zh-HK, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 59.33048433048433
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 15.0
      type: mozilla-foundation/common_voice_16_1
    metrics:
    - name: Wer
      type: wer
      value: 59.33048433048433
---

<!-- 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 v2

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 and the Common Voice 15.0 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.2720
- Wer: 59.3305

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2939        | 0.7918 | 1000 | 0.3060          | 65.9188 |
| 0.1498        | 1.5835 | 2000 | 0.2803          | 61.6809 |
| 0.0662        | 2.3753 | 3000 | 0.2720          | 59.3305 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1