---
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- hyojin99/EBRC
base_model: openai/whisper-base
model-index:
- name: ft_model
  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. -->

# ft_model

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co./openai/whisper-base) on the EBRC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4044
- Cer: 16.1170

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 6250
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4709        | 1.0   | 1250 | 0.4644          | 20.4829 |
| 0.2318        | 2.0   | 2500 | 0.3985          | 17.9464 |
| 0.1339        | 3.0   | 3750 | 0.3915          | 16.9433 |
| 0.0539        | 4.0   | 5000 | 0.3962          | 16.2937 |
| 0.0206        | 5.0   | 6250 | 0.4044          | 16.1170 |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2