---
language:
- kr
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- Jungwonchang/ksponspeech_partial
metrics:
- wer
base_model: openai/whisper-large-v2
model-index:
- name: Whisper large-v2, KsponSpeech Partial 10 epochs
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: KsponSpeech
      type: Jungwonchang/ksponspeech_partial
      config: eval
      split: test
      args: eval
    metrics:
    - type: wer
      value: 25.714073744343054
      name: Wer
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Jungwonchang/ksponspeech
      type: Jungwonchang/ksponspeech
      config: eval
      split: test
    metrics:
    - type: wer
      value: 25.54
      name: WER
---

<!-- 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 Partial 10 epochs

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: 0.0194
- Wer: 25.7141

## 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: 300

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2225        | 1.15  | 100  | 0.1394          | 27.9769 |
| 0.0507        | 3.11  | 200  | 0.0449          | 14.9640 |
| 0.0114        | 5.07  | 300  | 0.0194          | 25.7141 |


### Framework versions

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