whisper-hf-lora

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whisper-hf-lora

This model is a fine-tuned version of openai/whisper-large-v3-turbo on compulsion/heart-failure-audio. It achieves the following results on the evaluation set:

• Loss: 0.7572
• Wer: 0.2624

Model description

A PEFT LoRA adapter of whisper-large-v3-turbo finetuned on heart failure audio data that is conversational, longitudinal, and focused on chronic illness management and care coordination in a community-based healthcare setting.

Intended uses & limitations

To be used in ASR tasks specifically in the heart failure domain.

Benchmark (base whisper-large-v3-turbo vs. finetuned LoRA adapter)

Normalized for PHI redactions and throught Transformer's BasicTextNormalizer.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 4
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• 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: constant_with_warmup
• lr_scheduler_warmup_steps: 500
• num_epochs: 8
• mixed_precision_training: Native AMP

Training results

Framework versions

• PEFT 0.15.2
• Transformers 4.52.4
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1