metadata
base_model: openai/whisper-base
datasets:
- yoona-J/whisper_call_audio
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
model-index:
- name: Whisper_call
results: []
Whisper_call
This model is a fine-tuned version of openai/whisper-base on the whisper_call_audio dataset. It achieves the following results on the evaluation set:
- Loss: 0.5226
- Cer: 81.2616
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
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.8139 | 2.0 | 200 | 0.7714 | 37.8221 |
| 0.3977 | 4.0 | 400 | 0.4928 | 33.9313 |
| 0.1864 | 6.0 | 600 | 0.4458 | 78.8698 |
| 0.0907 | 8.0 | 800 | 0.4532 | 72.4187 |
| 0.0357 | 10.0 | 1000 | 0.4712 | 89.8265 |
| 0.015 | 12.0 | 1200 | 0.4899 | 88.2432 |
| 0.007 | 14.0 | 1400 | 0.5035 | 85.6325 |
| 0.0043 | 16.0 | 1600 | 0.5162 | 83.3839 |
| 0.0037 | 18.0 | 1800 | 0.5205 | 82.0448 |
| 0.0034 | 20.0 | 2000 | 0.5226 | 81.2616 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1