---
library_name: transformers
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- hyk000/woerae
model-index:
- name: wr_md
  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. -->

# wr_md

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the wr_ds dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4690
- Cer: 32.7677

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 2600
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.7558        | 3.8462 | 1000 | 1.0555          | 65.3794 |
| 0.0785        | 7.6923 | 2000 | 0.4690          | 32.7677 |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.5.0
- Datasets 3.0.2
- Tokenizers 0.20.1