---
library_name: peft
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-hf-rslora
  results: []
datasets:
- compulsi0n/heart-failure-audio
pipeline_tag: automatic-speech-recognition
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-hf-rslora

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on compulsion/heart-failure-audio.
It achieves the following results on the evaluation set:
- Loss: 0.6919
- Wer: 0.2424

## Model description

A PEFT rank-stablized 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 rank-stablized LoRA adapter)

Normalized for PHI redactions and throught Transformer's BasicTextNormalizer.

|   Model  | Raw WER (%) | Normalised WER (%) |
| :------: | :---------: | :----------------: |
| Baseline |    35.00    |        26.71       |
| rsLoRA   |    26.18    |        20.71       |

## 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

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.3062        | 1.0   | 92   | 1.1343          | 0.2388 |
| 1.0317        | 2.0   | 184  | 0.7145          | 0.2620 |
| 0.6833        | 3.0   | 276  | 0.6606          | 0.2105 |
| 0.5934        | 4.0   | 368  | 0.6292          | 0.2122 |
| 0.5104        | 5.0   | 460  | 0.6347          | 0.2521 |
| 0.4392        | 6.0   | 552  | 0.6444          | 0.2729 |
| 0.3653        | 7.0   | 644  | 0.6701          | 0.2198 |
| 0.3178        | 8.0   | 736  | 0.6919          | 0.2424 |


### Framework versions

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