metadata
language:
- zh
license: apache-2.0
library_name: peft
tags:
- hf-asr-leaderboard
- generated_from_trainer
base_model: openai/whisper-base
datasets:
- mozilla-foundation/common_voice_13_0
model-index:
- name: Whisper Base LoRA tuned zh-TW
results: []
pipeline_tag: automatic-speech-recognition
Whisper Base LoRA tuned zh-TW
DEMO LINK: https://4e766dca651b881c9b.gradio.live
This model is a fine-tuned version with PEFT-LoRA of openai/whisper-base on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3839
- CER: 22.13% :(
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: 4
- 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: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3981 | 1.0 | 1453 | 0.4017 |
| 0.4016 | 2.0 | 2906 | 0.3960 |
| 0.3543 | 3.0 | 4359 | 0.3933 |
| 0.3638 | 4.0 | 5812 | 0.3905 |
| 0.3953 | 5.0 | 7265 | 0.3895 |
| 0.377 | 6.0 | 8718 | 0.3879 |
| 0.3646 | 7.0 | 10171 | 0.3869 |
| 0.3592 | 8.0 | 11624 | 0.3860 |
| 0.3324 | 9.0 | 13077 | 0.3853 |
| 0.3818 | 10.0 | 14530 | 0.3848 |
| 0.3107 | 11.0 | 15983 | 0.3844 |
| 0.3473 | 12.0 | 17436 | 0.3844 |
| 0.3684 | 13.0 | 18889 | 0.3845 |
| 0.3886 | 14.0 | 20342 | 0.3841 |
| 0.3652 | 15.0 | 21795 | 0.3839 |
Framework versions
- PEFT 0.9.1.dev0
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2