---
language:
- ckb
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small Kurdish - Sorani
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: ckb
      split: test
      args: 'config: ckb, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 34.21226977606996
---

<!-- 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 Kurdish - Sorani

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3857
- Wer: 34.2123

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.4593        | 1.2330 | 1000 | 0.2504          | 42.2983 |
| 0.1318        | 2.4661 | 2000 | 0.2344          | 37.8429 |
| 0.0625        | 3.6991 | 3000 | 0.2582          | 35.9282 |
| 0.0274        | 4.9322 | 4000 | 0.2927          | 36.6139 |
| 0.009         | 6.1652 | 5000 | 0.3429          | 35.1365 |
| 0.0029        | 7.3983 | 6000 | 0.3625          | 34.7588 |
| 0.0008        | 8.6313 | 7000 | 0.3815          | 34.4740 |
| 0.0003        | 9.8644 | 8000 | 0.3857          | 34.2123 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1