metadata
library_name: transformers
language:
- nan
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small taiwanese
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: nan-tw
split: test
args: nan-tw
metrics:
- name: Wer
type: wer
value: 103.93735044594301
Whisper Small taiwanese
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.2406
- Wer: 103.9374
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-05
- train_batch_size: 64
- eval_batch_size: 8
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0007 | 39.005 | 1000 | 1.0996 | 97.8682 |
| 0.0003 | 79.005 | 2000 | 1.1532 | 100.1958 |
| 0.0001 | 119.005 | 3000 | 1.1976 | 102.4146 |
| 0.0001 | 159.005 | 4000 | 1.2206 | 105.9822 |
| 0.0001 | 199.005 | 5000 | 1.2406 | 103.9374 |
Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0