---
language:
- zh
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- edmundchan70/Cantonese_fine_tune
metrics:
- wer
model-index:
- name: Whisper Small fine tune-Edmund-0818
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Preach_speech_finetuning
      type: edmundchan70/Cantonese_fine_tune
      config: default
      split: train
      args: 'config: chinese, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 30.476190476190478
---

<!-- 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 fine tune-Edmund-0818

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Preach_speech_finetuning dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1966
- Wer: 30.4762

## 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: 1.25e-05
- train_batch_size: 16
- 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_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| No log        | 1.0   | 156  | 0.1196          | 17.1429 |
| No log        | 2.0   | 312  | 0.1553          | 24.6032 |
| No log        | 3.0   | 468  | 0.1655          | 26.5079 |
| 0.0806        | 4.0   | 624  | 0.1820          | 29.5238 |
| 0.0806        | 5.0   | 780  | 0.1792          | 30.1587 |
| 0.0806        | 6.0   | 936  | 0.1998          | 31.5873 |
| 0.0131        | 7.0   | 1092 | 0.1954          | 31.2698 |
| 0.0131        | 8.0   | 1248 | 0.1923          | 30.6349 |
| 0.0131        | 9.0   | 1404 | 0.1905          | 31.2698 |
| 0.0016        | 10.0  | 1560 | 0.1954          | 31.2698 |
| 0.0016        | 11.0  | 1716 | 0.1931          | 31.1111 |
| 0.0016        | 12.0  | 1872 | 0.1953          | 30.4762 |
| 0.0005        | 13.0  | 2028 | 0.1960          | 30.6349 |
| 0.0005        | 14.0  | 2184 | 0.1964          | 30.6349 |
| 0.0005        | 15.0  | 2340 | 0.1966          | 30.4762 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1