metadata

language:
  - id
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_17_0
metrics:
  - wer
model-index:
  - name: Whisper Medium Id - Rio Gunawan
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 17.0
          type: mozilla-foundation/common_voice_17_0
          config: id
          split: None
          args: 'config: id, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 12.877627732145344

Whisper Medium Id - Rio Gunawan

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

Loss: 0.2638
Wer: 12.8776

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: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1352	1.9231	1000	0.1943	13.3695
0.0167	3.8462	2000	0.2161	12.6131
0.0024	5.7692	3000	0.2483	12.5064
0.0008	7.6923	4000	0.2638	12.8776

Framework versions

Transformers 4.42.3
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1