| --- |
| language: |
| - ko |
| license: apache-2.0 |
| base_model: openai/whisper-base |
| tags: |
| - hf-asr-leaderboard |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: whisper_finetune |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # whisper_finetune |
| |
| This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the aihub_2 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3508 |
| - Cer: 12.0915 |
| - Wer: 35.6445 |
|
|
| ## 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: 32 |
| - eval_batch_size: 16 |
| - 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: 4000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:-------:|:---------------:|:-------:| |
| | 0.3416 | 0.32 | 500 | 12.9022 | 0.3510 | 36.6764 | |
| | 0.3344 | 0.64 | 1000 | 12.7008 | 0.3562 | 36.9463 | |
| | 0.3119 | 0.96 | 1500 | 12.4164 | 0.3517 | 36.5065 | |
| | 0.246 | 1.28 | 2000 | 12.4510 | 0.3569 | 36.4665 | |
| | 0.2437 | 1.6 | 2500 | 12.0823 | 0.3487 | 36.0543 | |
| | 0.2318 | 1.92 | 3000 | 0.3454 | 11.9698 | 35.7519 | |
| | 0.1861 | 2.24 | 3500 | 0.3501 | 11.9882 | 35.6895 | |
| | 0.1729 | 2.56 | 4000 | 0.3508 | 12.0915 | 35.6445 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.37.0.dev0 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
| |
