---
library_name: transformers
language:
- ar
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- darija-c
metrics:
- bleu
model-index:
- name: Finetuned Whisper large-v3-turbo0 for darija speech translation
  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. -->

# Finetuned Whisper large-v3-turbo0 for darija speech translation

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: 0.0003
- Bleu: 0.9369

## 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Bleu   |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 2.4675        | 2.2727  | 50   | 1.2036          | 0.2616 |
| 0.8385        | 4.5455  | 100  | 0.4859          | 0.5348 |
| 0.3255        | 6.8182  | 150  | 0.1448          | 0.7604 |
| 0.1266        | 9.0909  | 200  | 0.0588          | 0.8582 |
| 0.0654        | 11.3636 | 250  | 0.0501          | 0.8531 |
| 0.0427        | 13.6364 | 300  | 0.0336          | 0.8875 |
| 0.0315        | 15.9091 | 350  | 0.0209          | 0.9159 |
| 0.0188        | 18.1818 | 400  | 0.0214          | 0.8977 |
| 0.0193        | 20.4545 | 450  | 0.0103          | 0.9233 |
| 0.012         | 22.7273 | 500  | 0.0053          | 0.9329 |
| 0.0084        | 25.0    | 550  | 0.0089          | 0.9291 |
| 0.0072        | 27.2727 | 600  | 0.0028          | 0.9332 |
| 0.0031        | 29.5455 | 650  | 0.0042          | 0.9326 |
| 0.0032        | 31.8182 | 700  | 0.0045          | 0.9318 |
| 0.0026        | 34.0909 | 750  | 0.0005          | 0.9362 |
| 0.0008        | 36.3636 | 800  | 0.0004          | 0.9364 |
| 0.0006        | 38.6364 | 850  | 0.0003          | 0.9369 |
| 0.0003        | 40.9091 | 900  | 0.0003          | 0.9369 |
| 0.0003        | 43.1818 | 950  | 0.0003          | 0.9369 |
| 0.0003        | 45.4545 | 1000 | 0.0003          | 0.9369 |


### Framework versions

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