---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- razhan/DOLMA-speech
metrics:
- wer
model-index:
- name: whisper-base-sdh
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: razhan/DOLMA-speech southern_kurdish
      type: razhan/DOLMA-speech
      args: southern_kurdish
    metrics:
    - name: Wer
      type: wer
      value: 0.6882181444006173
---

<!-- 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-base-sdh

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the razhan/DOLMA-speech southern_kurdish dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6611
- Wer: 0.6882
- Cer: 0.2165

## 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: 192
- eval_batch_size: 128
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 384
- total_eval_batch_size: 256
- 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: 1
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 3.8394        | 1.0   | 16   | 1.9696          | 0.9849 | 0.6163 |
| 1.3507        | 2.0   | 32   | 1.0906          | 0.8956 | 0.4107 |
| 0.9898        | 3.0   | 48   | 0.7982          | 0.7872 | 0.2881 |
| 0.6834        | 4.0   | 64   | 0.6941          | 0.7153 | 0.2266 |
| 0.5981        | 5.0   | 80   | 0.6611          | 0.6882 | 0.2165 |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0