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---
library_name: transformers
language:
- ko
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- didiudom94/gentlemen
metrics:
- wer
model-index:
- name: Whisper Large-V2 Ko to En
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Gentlemen
type: didiudom94/gentlemen
args: 'split: train'
metrics:
- name: Wer
type: wer
value: 0.7335058679750543
---
<!-- 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 Large-V2 Ko to En
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Gentlemen dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0783
- Wer: 0.7335
## 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: 8
- 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: 400
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.2034 | 0.2253 | 1000 | 1.2714 | 0.7977 |
| 1.1758 | 0.4507 | 2000 | 1.1820 | 0.7810 |
| 1.1567 | 0.6760 | 3000 | 1.1158 | 0.7590 |
| 1.0885 | 0.9013 | 4000 | 1.0783 | 0.7335 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
|