---
library_name: transformers
language:
- ko
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- Suchae/whisper-large-v3-ko-middlesenior-dialect-speech-v1.1
model-index:
- name: Suchae/whisper-large-v3-ko-middlesenior-dialect-speech-v1.1
  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. -->

# Suchae/whisper-large-v3-ko-middlesenior-dialect-speech-v1.1

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Suchae/whisper-large-v3-ko-middlesenior-dialect-speech-v1.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5249
- Cer: 14.4500

## 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-06
- train_batch_size: 10
- eval_batch_size: 5
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.333         | 0.0548 | 64   | 0.9131          | 19.4136 |
| 1.1099        | 0.1096 | 128  | 0.7550          | 17.2538 |
| 0.9577        | 0.1643 | 192  | 0.6955          | 17.2038 |
| 0.9198        | 0.2191 | 256  | 0.6615          | 15.8003 |
| 0.7995        | 0.2739 | 320  | 0.6357          | 16.5130 |
| 0.7898        | 0.3287 | 384  | 0.6150          | 15.8066 |
| 0.7344        | 0.3835 | 448  | 0.6022          | 14.9533 |
| 0.7035        | 0.4383 | 512  | 0.5846          | 14.3594 |
| 0.6936        | 0.4930 | 576  | 0.5711          | 16.6193 |
| 0.6427        | 0.5478 | 640  | 0.5602          | 14.7063 |
| 0.6365        | 0.6026 | 704  | 0.5530          | 15.0095 |
| 0.6107        | 0.6574 | 768  | 0.5440          | 14.5813 |
| 0.596         | 0.7122 | 832  | 0.5379          | 15.2315 |
| 0.5831        | 0.7670 | 896  | 0.5357          | 15.1377 |
| 0.5542        | 0.8217 | 960  | 0.5308          | 15.0314 |
| 0.5675        | 0.8765 | 1024 | 0.5277          | 15.2252 |
| 0.532         | 0.9313 | 1088 | 0.5252          | 15.6722 |
| 0.5255        | 0.9861 | 1152 | 0.5249          | 14.4500 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu118
- Datasets 3.0.0
- Tokenizers 0.19.1