---
library_name: transformers
language:
- ar
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- whisper-large-v3-turbo
- generated_from_trainer
datasets:
- darija-c
metrics:
- bleu
model-index:
- name: whisper-large-v3-turbo-darija-st
  results: []
---

<!-- 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-darija-st

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Darija-C dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4484
- Bleu: 0.1506

## 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 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.5028        | 12.5  | 50   | 7.3272          | 0.0    |
| 6.3107        | 25.0  | 100  | 5.5738          | 0.0    |
| 5.3612        | 37.5  | 150  | 5.0667          | 0.0    |
| 4.9035        | 50.0  | 200  | 4.5926          | 0.0    |
| 4.3264        | 62.5  | 250  | 3.9335          | 0.0    |
| 3.5805        | 75.0  | 300  | 3.1526          | 0.0    |
| 2.7738        | 87.5  | 350  | 2.4034          | 0.0045 |
| 2.1907        | 100.0 | 400  | 2.0046          | 0.0099 |
| 1.8861        | 112.5 | 450  | 1.7903          | 0.0095 |
| 1.6974        | 125.0 | 500  | 1.5375          | 0.0072 |
| 1.4036        | 137.5 | 550  | 1.2622          | 0.0118 |
| 1.1448        | 150.0 | 600  | 1.0376          | 0.0024 |
| 0.95          | 162.5 | 650  | 0.8782          | 0.0208 |
| 0.8016        | 175.0 | 700  | 0.7391          | 0.0800 |
| 0.6971        | 187.5 | 750  | 0.6580          | 0.0836 |
| 0.6094        | 200.0 | 800  | 0.5693          | 0.1410 |
| 0.5455        | 212.5 | 850  | 0.5185          | 0.1336 |
| 0.4971        | 225.0 | 900  | 0.4791          | 0.1210 |
| 0.4654        | 237.5 | 950  | 0.4571          | 0.1636 |
| 0.4471        | 250.0 | 1000 | 0.4484          | 0.1506 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 2.19.2
- Tokenizers 0.21.0