---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- ylacombe/english_dialects
metrics:
- wer
model-index:
- name: Whisper Small Dv - khaled lakhdher
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ylacombe/english_dialects
      type: ylacombe/english_dialects
    metrics:
    - name: Wer
      type: wer
      value: 6.0064935064935066
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small Dv - khaled lakhdher

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ylacombe/english_dialects dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2430
- Wer Ortho: 6.5898
- Wer: 6.0065

## 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: 16
- 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: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|
| 0.0002        | 19.2308 | 500  | 0.2430          | 6.5898    | 6.0065 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0