---
library_name: transformers
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- jindol/debugged_03_Whisper_datasets
model-index:
- name: repo_name
  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. -->

# repo_name

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the debugged_03_Whisper_datasets dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6540
- Cer: 32.5714

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0001        | 500.0  | 1000 | 1.4956          | 32.5714 |
| 0.0001        | 1000.0 | 2000 | 1.5831          | 36.0    |
| 0.0           | 1500.0 | 3000 | 1.6306          | 32.5714 |
| 0.0           | 2000.0 | 4000 | 1.6540          | 32.5714 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.0.1
- Datasets 3.1.0
- Tokenizers 0.20.3