---
library_name: transformers
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-augmented-ft-1
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-augmented
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: ntnu-smil/lttc-augmented-ft-1
      type: ntnu-smil/lttc-augmented-ft-1
    metrics:
    - type: wer
      value: 32.36001374098248
      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-augmented

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-augmented-ft-1 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3566
- Wer: 32.3600
- Cer: 18.4747

## 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: 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
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.0483        | 1.0   | 190  | 1.2801          | 35.8640 | 20.7045 |
| 0.0503        | 2.0   | 380  | 1.3510          | 32.5318 | 20.3283 |
| 0.0033        | 3.0   | 570  | 1.2776          | 39.3336 | 22.9891 |
| 0.0007        | 4.0   | 760  | 1.3057          | 32.6692 | 18.6594 |
| 0.0002        | 5.0   | 950  | 1.3566          | 32.3600 | 18.4747 |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0