metadata
library_name: transformers
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- jwh1449/AIhub_foreign_dataset4
model-index:
- name: whisper_base_test
results: []
whisper_base_test
This model is a fine-tuned version of openai/whisper-base on the AIhub_foreign_dataset4 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9395
- Cer: 48.1817
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 1.0479 | 0.7299 | 1000 | 0.9942 | 53.5695 |
| 0.983 | 1.4599 | 2000 | 0.9553 | 50.5824 |
| 0.7329 | 2.1898 | 3000 | 0.9432 | 56.3785 |
| 0.7979 | 2.9197 | 4000 | 0.9299 | 48.6001 |
| 0.6956 | 3.6496 | 5000 | 0.9368 | 47.2723 |
| 0.5971 | 4.3796 | 6000 | 0.9395 | 48.1817 |
Framework versions
- Transformers 4.51.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1