---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- AIHub
model-index:
- name: test
  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. -->

# test

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Voice data of foreigners speaking Korean for AI learning dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5120
- Cer: 22.3647

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0055        | 18.87 | 1000 | 0.4457          | 22.0218 |
| 0.0009        | 37.74 | 2000 | 0.4855          | 21.6916 |
| 0.0005        | 56.6  | 3000 | 0.5046          | 20.6502 |
| 0.0004        | 75.47 | 4000 | 0.5120          | 22.3647 |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1