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---
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
|