---
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-2
  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: 36.52802893309223
      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-2

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: 3.7199
- Wer: 36.5280
- Cer: 25.0

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.0489        | 1.0   | 18   | 3.2509          | 37.2514 | 23.4504 |
| 0.1246        | 2.0   | 36   | 3.6744          | 35.6239 | 23.5709 |
| 0.0011        | 3.0   | 54   | 3.6182          | 36.7089 | 22.9855 |
| 0.0075        | 4.0   | 72   | 3.7182          | 37.1609 | 22.6240 |
| 0.0002        | 5.0   | 90   | 3.7643          | 37.7939 | 23.6398 |
| 0.0028        | 6.0   | 108  | 3.6117          | 36.7089 | 23.8809 |
| 0.0003        | 7.0   | 126  | 3.5535          | 36.8897 | 24.6556 |
| 0.0001        | 8.0   | 144  | 3.6586          | 37.7939 | 25.1033 |
| 0.0003        | 9.0   | 162  | 3.6168          | 36.8897 | 24.7934 |
| 0.0001        | 10.0  | 180  | 3.6500          | 37.1609 | 25.1033 |
| 0.0002        | 11.0  | 198  | 3.6934          | 37.4322 | 25.3960 |
| 0.0001        | 12.0  | 216  | 3.6901          | 36.9801 | 25.2410 |
| 0.0001        | 13.0  | 234  | 3.6980          | 36.7993 | 25.2238 |
| 0.0001        | 14.0  | 252  | 3.6990          | 36.9801 | 25.1377 |
| 0.0002        | 15.0  | 270  | 3.7110          | 36.9801 | 25.2755 |
| 0.0001        | 16.0  | 288  | 3.7139          | 36.7993 | 25.1894 |
| 0.0001        | 17.0  | 306  | 3.7175          | 36.7089 | 25.1722 |
| 0.0001        | 18.0  | 324  | 3.7202          | 36.9801 | 25.3444 |
| 0.0001        | 19.0  | 342  | 3.7210          | 36.8897 | 24.9828 |
| 0.0002        | 20.0  | 360  | 3.7199          | 36.5280 | 25.0    |


### Framework versions

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