---
library_name: transformers
license: mit
base_model: unsloth/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- haitian-creole-asr
metrics:
- wer
model-index:
- name: Ayira Large Turbo V3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Haitian Creole ASR Dataset
      type: haitian-creole-asr
      args: 'language: ht, split: train'
    metrics:
    - name: Wer
      type: wer
      value: 5.613132085970648
---

<!-- 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. -->

# Ayira Large Turbo V3

This model is a fine-tuned version of [unsloth/whisper-large-v3-turbo](https://huggingface.co/unsloth/whisper-large-v3-turbo) on the Haitian Creole ASR Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2041
- Wer: 5.6131

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- 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: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0906        | 2.9499  | 1000 | 0.1945          | 15.4483 |
| 0.0296        | 5.8997  | 2000 | 0.1862          | 6.4095  |
| 0.0032        | 8.8496  | 3000 | 0.1946          | 5.6375  |
| 0.0004        | 11.7994 | 4000 | 0.2041          | 5.6131  |


### Framework versions

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