---
base_model: openai/whisper-base
datasets:
- Jpep26/AfterProcessing
language:
- ko
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- hf-asr-leaderboard
- generated_from_trainer
model-index:
- name: Test
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: AfterProcessing
      type: Jpep26/AfterProcessing
      args: 'config: ko, split: valid'
    metrics:
    - type: wer
      value: 0.7054380664652568
      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. -->

# Test

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the AfterProcessing dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9167
- Cer: 0.8486
- Wer: 0.7054
- Mean: 0.7770

## 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: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer    | Wer    | Mean   |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|
| 2.9457        | 0.6410 | 50   | 2.6739          | 0.5791 | 0.8056 | 0.6923 |
| 1.7821        | 1.2821 | 100  | 1.6827          | 0.4622 | 0.6561 | 0.5592 |
| 1.2153        | 1.9231 | 150  | 1.1411          | 0.4216 | 0.6022 | 0.5119 |
| 0.8636        | 2.5641 | 200  | 0.9167          | 0.8486 | 0.7054 | 0.7770 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1