---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- hyojin99/EBRC
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: 0.1886
- Cer: 10.6428

## 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: 50
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3649        | 0.4   | 1000 | 0.3399          | 18.5291 |
| 0.2559        | 0.8   | 2000 | 0.2578          | 14.4563 |
| 0.1746        | 1.2   | 3000 | 0.2247          | 13.3580 |
| 0.1639        | 1.6   | 4000 | 0.2017          | 11.5004 |
| 0.1251        | 2.0   | 5000 | 0.1909          | 10.8103 |
| 0.1051        | 2.4   | 6000 | 0.1886          | 10.6428 |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2