---
library_name: peft
language:
- en
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- wft
- whisper
- automatic-speech-recognition
- audio
- speech
- generated_from_trainer
datasets:
- ntnu-smil/lttc-rebalanced-1-split
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-score-5-rebalanced-1
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: ntnu-smil/lttc-rebalanced-1-split
      type: ntnu-smil/lttc-rebalanced-1-split
    metrics:
    - type: wer
      value: 39.732142857142854
      name: Wer
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# whisper-large-v3-turbo-score-5-rebalanced-1

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the ntnu-smil/lttc-rebalanced-1-split dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9922
- Wer: 39.7321
- Cer: 25.9187

## 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: 0.0005
- train_batch_size: 4
- 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
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.0378        | 1.0   | 18   | 3.6518          | 40.3159 | 26.1279 |
| 0.0389        | 2.0   | 36   | 3.8285          | 40.0412 | 26.6444 |
| 0.0023        | 3.0   | 54   | 4.0319          | 40.4876 | 26.5529 |
| 0.0021        | 4.0   | 72   | 3.9976          | 39.3544 | 25.5656 |
| 0.0004        | 5.0   | 90   | 3.9922          | 39.7321 | 25.9187 |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3