---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- Jinho11/jinho_data_2023-11-19
model-index:
- name: Kim_Sohn_Whisper
  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. -->

# Kim_Sohn_Whisper

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the jinho_data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6363
- Cer: 15.4890

## 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
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3344        | 2.43  | 1000 | 0.5535          | 19.6948 |
| 0.1546        | 4.85  | 2000 | 0.5602          | 16.2194 |
| 0.0505        | 7.28  | 3000 | 0.6095          | 15.7197 |
| 0.0266        | 9.71  | 4000 | 0.6363          | 15.4890 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0