---
library_name: transformers
language:
- nan
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Hokkien-to-Tai Lo Whisper ver 2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.0
      type: mozilla-foundation/common_voice_16_1
      config: nan-tw
      split: test
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 137.93654416799816
---

<!-- 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 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: 0.6832
- Wer: 137.9365

## 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      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 5.7216        | 0.2581 | 800  | 1.5008          | 134.0105 |
| 1.1329        | 0.5161 | 1600 | 1.0312          | 125.0399 |
| 0.9625        | 0.7742 | 2400 | 0.8906          | 127.3682 |
| 0.8124        | 1.0323 | 3200 | 0.7961          | 132.3214 |
| 0.7005        | 1.2903 | 4000 | 0.7438          | 127.8703 |
| 0.6735        | 1.5484 | 4800 | 0.7058          | 132.8920 |
| 0.632         | 1.8065 | 5600 | 0.6832          | 137.9365 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0