---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- rab796/whisper_finetune_md_240120
model-index:
- name: Whisper Base finetune - rab796
  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 Base finetune - rab796

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the whisper_finetune_data2_240120 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3989
- Cer: 27.6596

## 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: 4000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0001        | 500.0  | 1000 | 1.3218          | 26.9504 |
| 0.0           | 1000.0 | 2000 | 1.3690          | 27.3050 |
| 0.0           | 1500.0 | 3000 | 1.3913          | 27.6596 |
| 0.0           | 2000.0 | 4000 | 1.3989          | 27.6596 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0