---
base_model: openai/whisper-base
datasets:
- yoona-J/whisper_call_audio
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
model-index:
- name: Whisper_call
  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. -->

# Whisper_call

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the whisper_call_audio dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5226
- Cer: 81.2616

## 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.8139        | 2.0   | 200  | 0.7714          | 37.8221 |
| 0.3977        | 4.0   | 400  | 0.4928          | 33.9313 |
| 0.1864        | 6.0   | 600  | 0.4458          | 78.8698 |
| 0.0907        | 8.0   | 800  | 0.4532          | 72.4187 |
| 0.0357        | 10.0  | 1000 | 0.4712          | 89.8265 |
| 0.015         | 12.0  | 1200 | 0.4899          | 88.2432 |
| 0.007         | 14.0  | 1400 | 0.5035          | 85.6325 |
| 0.0043        | 16.0  | 1600 | 0.5162          | 83.3839 |
| 0.0037        | 18.0  | 1800 | 0.5205          | 82.0448 |
| 0.0034        | 20.0  | 2000 | 0.5226          | 81.2616 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1