metadata

library_name: transformers
language:
  - ko
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - generated_from_trainer
datasets:
  - didiudom94/gentlemen2
metrics:
  - wer
model-index:
  - name: Whisper Large-V3 Ko to En
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Gentlemen
          type: didiudom94/gentlemen2
          args: 'split: train'
        metrics:
          - name: Wer
            type: wer
            value: 0.7630289773857083

Whisper Large-V3 Ko to En

This model is a fine-tuned version of openai/whisper-large-v3 on the Gentlemen dataset. It achieves the following results on the evaluation set:

Loss: 1.1304
Wer: 0.7630

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: 5e-06
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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.2511	0.4507	1000	1.2619	0.7806
1.1681	0.9013	2000	1.1703	0.7751
0.9217	1.3520	3000	1.1486	0.7768
0.9093	1.8026	4000	1.1304	0.7630

Framework versions

Transformers 4.45.2
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.20.3