metadata
library_name: transformers
language:
- nan
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_12_0
metrics:
- wer
model-index:
- name: Hokkien-to-Tai Lo Whisper ver 1.1
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 16.0
type: mozilla-foundation/common_voice_12_0
config: nan-tw
split: test
args: 'config: hi, split: test'
metrics:
- type: wer
value: 133.72270187912648
name: Wer
Hokkien-to-Tai Lo Whisper ver 1.1
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7563
- Wer: 133.7227
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 |
|---|---|---|---|---|
| 5.7198 | 0.5135 | 800 | 1.4813 | 136.8207 |
| 1.1293 | 1.0270 | 1600 | 1.0268 | 128.2885 |
| 0.9323 | 1.5404 | 2400 | 0.8802 | 131.1833 |
| 0.7797 | 2.0539 | 3200 | 0.8011 | 132.2499 |
| 0.6692 | 2.5674 | 4000 | 0.7563 | 133.7227 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0