---
library_name: transformers
language:
- nan
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Hokkien-to-Tai Lo Whisper ver 4
  results:
  - task:
      name: Automatic Speech Recognition
      type: 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:
    - name: Wer
      type: wer
      value: 84.17395202869312
---

<!-- 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 4

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4709
- Wer: 84.1740

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3834        | 0.256 | 800  | 0.5102          | 83.2549 |
| 0.4023        | 0.512 | 1600 | 0.4974          | 82.0220 |
| 0.4024        | 0.768 | 2400 | 0.4877          | 83.6808 |
| 0.3819        | 1.024 | 3200 | 0.4820          | 80.9460 |
| 0.3125        | 1.28  | 4000 | 0.4772          | 79.4889 |
| 0.315         | 1.536 | 4800 | 0.4762          | 82.0220 |
| 0.3057        | 1.792 | 5600 | 0.4707          | 80.2062 |
| 0.3093        | 2.048 | 6400 | 0.4695          | 82.0444 |
| 0.2507        | 2.304 | 7200 | 0.4716          | 83.4342 |
| 0.2476        | 2.56  | 8000 | 0.4709          | 84.1740 |


### Framework versions

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