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# whisper_medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the aihub_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2566
- Cer: 9.1657
- Wer: 27.2418

## 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-07
- train_batch_size: 4
- 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
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 2.4204        | 0.04  | 500  | 2.2566          | 9.1657 | 27.2418 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0

{"language": ["ko"], "license": "apache-2.0", "tags": ["hf-asr-leaderboard", "generated_from_trainer"], "metrics": ["wer"], "base_model": "openai/whisper-medium", "model-index": [{"name": "whisper_medium", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ko base_model:openai/whisper-medium license:apache-2.0 endpoints_compatible region:us