---
library_name: transformers
language:
- nan
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Hokkien-to-Tai Lo Whisper ver 1.2
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 16.0
      type: mozilla-foundation/common_voice_17_0
      config: nan-tw
      split: test
      args: 'config: hi, split: test'
    metrics:
    - type: wer
      value: 127.25846222819996
      name: Wer
---

<!-- 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. -->

# Hokkien-to-Tai Lo Whisper ver 1.2

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6145
- Wer: 127.2585

## 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-06
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9814        | 0.256 | 800  | 0.9274          | 132.0108 |
| 0.8335        | 0.512 | 1600 | 0.8062          | 128.4465 |
| 0.7856        | 0.768 | 2400 | 0.7318          | 131.0020 |
| 0.6938        | 1.024 | 3200 | 0.6892          | 127.7740 |
| 0.6089        | 1.28  | 4000 | 0.6609          | 125.5100 |
| 0.6078        | 1.536 | 4800 | 0.6377          | 128.8276 |
| 0.5756        | 1.792 | 5600 | 0.6244          | 126.0031 |
| 0.5764        | 2.048 | 6400 | 0.6145          | 127.2585 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0