| --- |
| language: |
| - ko |
| license: apache-2.0 |
| tags: |
| - hf-asr-leaderboard |
| - generated_from_trainer |
| metrics: |
| - wer |
| base_model: openai/whisper-large-v2 |
| 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-large-v2](https://huggingface.co/openai/whisper-large-v2) on the aihub_100000 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1966 |
| - Cer: 5.9236 |
| - Wer: 23.0770 |
|
|
| ## 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-06 |
| - train_batch_size: 16 |
| - 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 | |
| |:-------------:|:-----:|:----:|:------:|:---------------:|:-------:| |
| | 0.1866 | 0.16 | 1000 | 6.0386 | 0.1963 | 23.2684 | |
| | 0.1788 | 0.32 | 2000 | 6.0483 | 0.1979 | 23.2267 | |
| | 0.1541 | 0.48 | 3000 | 6.0116 | 0.1929 | 23.5519 | |
| | 0.1692 | 0.64 | 4000 | 0.1966 | 5.9236 | 23.0770 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.38.0.dev0 |
| - Pytorch 1.14.0a0+410ce96 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.1 |
| |
