transformers safetensors whisper automatic-speech-recognition generated_from_trainer ar dataset:darija-c base_model:openai/whisper-large-v3-turbo base_model:finetune:openai/whisper-large-v3-turbo license:mit endpoints_compatible region:us
---
base_model: openai/whisper-large-v3-turbo
datasets:
- darija-c
language:
- ar
library_name: transformers
license: mit
metrics:
- bleu
tags:
- generated_from_trainer
model-index:
- name: Finetuned Whisper large-v3-turbo for darija speech translation
  results: []
---

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# Finetuned Whisper large-v3-turbo 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: 0.0004
- Bleu: 0.8080

## 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   |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 2.4688        | 2.2727  | 50   | 2.1049          | 0.0694 |
| 0.8484        | 4.5455  | 100  | 0.9947          | 0.1871 |
| 0.3358        | 6.8182  | 150  | 0.2579          | 0.5827 |
| 0.1395        | 9.0909  | 200  | 0.0936          | 0.6840 |
| 0.0669        | 11.3636 | 250  | 0.0383          | 0.7778 |
| 0.0421        | 13.6364 | 300  | 0.0214          | 0.7793 |
| 0.0293        | 15.9091 | 350  | 0.0195          | 0.8053 |
| 0.0228        | 18.1818 | 400  | 0.0102          | 0.8019 |
| 0.0132        | 20.4545 | 450  | 0.0065          | 0.8014 |
| 0.011         | 22.7273 | 500  | 0.0050          | 0.8053 |
| 0.0094        | 25.0    | 550  | 0.0025          | 0.8080 |
| 0.0048        | 27.2727 | 600  | 0.0009          | 0.8080 |
| 0.002         | 29.5455 | 650  | 0.0007          | 0.8080 |
| 0.0011        | 31.8182 | 700  | 0.0005          | 0.8080 |
| 0.0007        | 34.0909 | 750  | 0.0005          | 0.8080 |
| 0.0006        | 36.3636 | 800  | 0.0004          | 0.8080 |
| 0.0004        | 38.6364 | 850  | 0.0004          | 0.8080 |
| 0.0003        | 40.9091 | 900  | 0.0004          | 0.8080 |
| 0.0002        | 43.1818 | 950  | 0.0004          | 0.8080 |
| 0.0002        | 45.4545 | 1000 | 0.0004          | 0.8080 |


### Framework versions

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