---
language:
- kr
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- Jungwonchang/ksponspeech
metrics:
- wer
model-index:
- name: Whisper large-v2, KsponSpeech
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: KsponSpeech
      type: Jungwonchang/ksponspeech
      config: dev
      split: validation
      args: dev
    metrics:
    - name: Wer
      type: wer
      value: 42.225687000584685
---

<!-- 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 large-v2, KsponSpeech

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the KsponSpeech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2946
- Wer: 42.2257

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3315        | 0.25  | 500  | 0.3446          | 41.5319 |
| 0.3204        | 0.5   | 1000 | 0.3229          | 37.7003 |
| 0.2967        | 0.75  | 1500 | 0.3054          | 38.3980 |
| 0.2859        | 1.0   | 2000 | 0.2946          | 42.2257 |


### Framework versions

- Transformers 4.31.0
- Pytorch 1.12.1+cu116
- Datasets 2.14.0
- Tokenizers 0.12.1