---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- tachelhit_darija
metrics:
- wer
model-index:
- name: whisper-small-darija
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: tachelhit_darija
      type: tachelhit_darija
      config: default
      split: None
      args: default
    metrics:
    - type: wer
      value: 27.93522267206478
      name: Wer
---

<!-- 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

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the tachelhit_darija dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3828
- Wer: 27.9352

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

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.572         | 1.4286  | 100  | 0.6403          | 60.7287 |
| 0.2156        | 2.8571  | 200  | 0.4233          | 42.7800 |
| 0.0459        | 4.2857  | 300  | 0.3953          | 48.1781 |
| 0.0257        | 5.7143  | 400  | 0.3663          | 31.0391 |
| 0.0089        | 7.1429  | 500  | 0.3857          | 31.9838 |
| 0.0029        | 8.5714  | 600  | 0.3748          | 30.3644 |
| 0.0026        | 10.0    | 700  | 0.3756          | 29.4197 |
| 0.0012        | 11.4286 | 800  | 0.3801          | 27.5304 |
| 0.0011        | 12.8571 | 900  | 0.3821          | 27.9352 |
| 0.0013        | 14.2857 | 1000 | 0.3828          | 27.9352 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0