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# whisper-chimsuja

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the potatoSeop/chimsuja_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3795
- Cer: 12.0513

## 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
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.913         | 0.4   | 50   | 0.4665          | 14.4249 |
| 0.4203        | 0.79  | 100  | 0.4156          | 18.1852 |
| 0.343         | 1.19  | 150  | 0.3972          | 13.9544 |
| 0.2746        | 1.59  | 200  | 0.3891          | 13.2048 |
| 0.2838        | 1.98  | 250  | 0.3827          | 13.8794 |
| 0.2153        | 2.38  | 300  | 0.3808          | 12.0721 |
| 0.2035        | 2.78  | 350  | 0.3795          | 12.0513 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0

{"language": ["ko"], "license": "apache-2.0", "tags": ["hf-asr-leaderboard", "generated_from_trainer"], "datasets": ["potatoSeop/chimsuja_dataset"], "base_model": "openai/whisper-base", "model-index": [{"name": "whisper-chimsuja", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ko dataset:potatoSeop/chimsuja_dataset base_model:openai/whisper-base license:apache-2.0 endpoints_compatible region:us