whisper-small-hy-cv20.0

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Whisper Small Hy - Erik Mkrtchyan

This model is a fine-tuned version of openai/whisper-small on the Hy Generated Audio Data with CV 20.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.1685
• Wer: 36.7015

Model description

This model is based on OpenAI's Whisper Small and fine-tuned for Armenian using exclusively real audio data. It is designed to transcribe Armenian speech into text and serves as a benchmark to evaluate how well the model learns using only real (non-synthetic) data.

Training and evaluation data

The dataset contains both real and high-quality synthetic Armenian speech clips.

Total duration: ~31 hours
Train set duration(train+generated): ~13 hours
Test set duration(test+eval) ~18 hours

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 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
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.51.3
• Pytorch 2.7.0+cu126
• Datasets 3.6.0
• Tokenizers 0.21.1