metadata
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
Hokkien-to-Tai Lo Whisper ver 4
This model is a fine-tuned version of 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