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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
model-index:
- name: gwanju_large2_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. -->
# gwanju_large2_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: 0.3321
- Cer: 438.5339
## 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 | Cer |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4681 | 0.0741 | 250 | 0.4882 | 92.4888 |
| 0.4609 | 0.1482 | 500 | 0.4507 | 180.4507 |
| 0.4749 | 0.2223 | 750 | 0.4351 | 148.4249 |
| 0.4248 | 0.2964 | 1000 | 0.4260 | 50.0864 |
| 0.4433 | 0.3705 | 1250 | 0.3998 | 107.5518 |
| 0.3667 | 0.4446 | 1500 | 0.3907 | 296.2817 |
| 0.3805 | 0.5187 | 1750 | 0.3795 | 308.2578 |
| 0.3571 | 0.5928 | 2000 | 0.3770 | 396.0998 |
| 0.4312 | 0.6669 | 2250 | 0.3644 | 470.9584 |
| 0.3445 | 0.7410 | 2500 | 0.3562 | 392.7995 |
| 0.4036 | 0.8151 | 2750 | 0.3485 | 468.5345 |
| 0.3523 | 0.8892 | 3000 | 0.3426 | 459.9051 |
| 0.3541 | 0.9632 | 3250 | 0.3377 | 456.2648 |
| 0.2252 | 1.0373 | 3500 | 0.3343 | 450.6082 |
| 0.2063 | 1.1114 | 3750 | 0.3333 | 444.6852 |
| 0.2018 | 1.1855 | 4000 | 0.3321 | 438.5339 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.2.2+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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