---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- Custom_activation_from_scratch train_whisper(12layerschange,10000_2000_2000_200)
- generated_from_trainer
datasets:
- darija-c
metrics:
- bleu
model-index:
- name: 'Whisper small darija translate '
  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 small darija translate 

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Darija-C dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Bleu: 0.0681

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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: 2000
- training_steps: 16000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch     | Step  | Validation Loss | Bleu   |
|:-------------:|:---------:|:-----:|:---------------:|:------:|
| 0.6324        | 133.3333  | 2000  | 0.5772          | 0.0    |
| 0.2913        | 266.6667  | 4000  | 0.2546          | 0.1229 |
| 0.2803        | 400.0     | 6000  | 0.2447          | 0.0859 |
| 0.2342        | 533.3333  | 8000  | 0.2505          | 0.0428 |
| 0.0562        | 666.6667  | 10000 | 0.0231          | 0.1789 |
| 0.0002        | 800.0     | 12000 | 0.0002          | 0.1136 |
| 0.0001        | 933.3333  | 14000 | 0.0001          | 0.0681 |
| 0.0001        | 1066.6667 | 16000 | 0.0001          | 0.0681 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 2.19.2
- Tokenizers 0.20.3