metadata
language:
- nan
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small Taiwanese
results: []
Whisper Small Taiwanese
This model is a fine-tuned version of openai/whisper-small on the Common Voice 15.0 and 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3916
- Wer: 68.5703
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4172 | 0.32 | 1000 | 0.4641 | 82.9494 |
| 0.2962 | 0.64 | 2000 | 0.3834 | 73.8040 |
| 0.229 | 0.97 | 3000 | 0.3537 | 70.0423 |
| 0.1994 | 1.29 | 4000 | 0.3685 | 71.1599 |
| 0.1693 | 1.61 | 5000 | 0.3551 | 67.8206 |
| 0.1398 | 1.93 | 6000 | 0.3526 | 67.6707 |
| 0.1032 | 2.25 | 7000 | 0.3836 | 69.4834 |
| 0.0745 | 2.58 | 8000 | 0.3839 | 68.5566 |
| 0.0558 | 2.9 | 9000 | 0.3916 | 68.5703 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2