metadata

library_name: transformers
language:
  - hu
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_17_0
metrics:
  - wer
model-index:
  - name: TcT Whisper Turbo - Zakryah
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common voice 17.0
          type: mozilla-foundation/common_voice_17_0
          config: hu
          split: test
          args: 'config: hu, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 10.865284788601295

TcT Whisper Turbo - Zakryah

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common voice 17.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.1012
Wer: 10.8653

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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
0.1832	0.3299	1000	0.1836	18.5993
0.1546	0.6598	2000	0.1450	15.8307
0.1182	0.9898	3000	0.1138	12.4178
0.0435	1.3197	4000	0.1012	10.8653

Framework versions

Transformers 4.53.0.dev0
Pytorch 2.5.1
Datasets 3.3.2
Tokenizers 0.21.1