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---
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
base_model: openai/whisper-large
datasets:
- Marcusxx/gwanju
metrics:
- wer
model-index:
- name: gwanju_largeWER_model
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Marcusxx/gwanju
type: Marcusxx/gwanju
args: 'config: ko, split: valid'
metrics:
- type: wer
value: 41.85458286890166
name: Wer
---
<!-- 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. -->
# gwanju_largeWER_model
This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Marcusxx/gwanju dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3334
- Wer: 41.8546
## 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: 100
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4683 | 0.0741 | 250 | 0.4884 | 104.4328 |
| 0.4578 | 0.1482 | 500 | 0.4522 | 55.8304 |
| 0.4675 | 0.2223 | 750 | 0.4379 | 65.3948 |
| 0.4338 | 0.2964 | 1000 | 0.4225 | 65.4206 |
| 0.4547 | 0.3705 | 1250 | 0.4023 | 63.5814 |
| 0.3676 | 0.4446 | 1500 | 0.3914 | 47.9551 |
| 0.3752 | 0.5187 | 1750 | 0.3840 | 48.3838 |
| 0.3584 | 0.5928 | 2000 | 0.3745 | 44.8641 |
| 0.4221 | 0.6669 | 2250 | 0.3638 | 42.4548 |
| 0.3432 | 0.7410 | 2500 | 0.3563 | 42.7206 |
| 0.3993 | 0.8151 | 2750 | 0.3497 | 44.7955 |
| 0.3448 | 0.8892 | 3000 | 0.3437 | 43.3722 |
| 0.3441 | 0.9632 | 3250 | 0.3381 | 40.4270 |
| 0.2317 | 1.0373 | 3500 | 0.3350 | 39.5782 |
| 0.2063 | 1.1114 | 3750 | 0.3339 | 40.8385 |
| 0.2016 | 1.1855 | 4000 | 0.3334 | 41.8546 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.2.2+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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