metadata
language:
- nan
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
model-index:
- name: Whisper Small Taiwanese - hanzi
results: []
Whisper Small Taiwanese - hanzi
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2705
- Cer: 16.2525
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.2
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss |
|---|---|---|---|---|
| 0.5463 | 0.4 | 1000 | 28.5221 | 0.5585 |
| 0.4142 | 0.8 | 2000 | 24.6764 | 0.4017 |
| 0.2268 | 1.2 | 3000 | 19.0744 | 0.3413 |
| 0.2183 | 1.6 | 4000 | 18.1837 | 0.3093 |
| 0.2223 | 2.0 | 5000 | 0.2952 | 17.1932 |
| 0.125 | 2.4 | 6000 | 0.2840 | 17.1016 |
| 0.118 | 2.8 | 7000 | 0.2734 | 16.8893 |
| 0.0678 | 3.2 | 8000 | 0.2705 | 16.2525 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1