---
language:
- ckb
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Ckb - Razhan Hameed
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: ckb
      split: test
    metrics:
    - name: Wer
      type: wer
      value: 33.2192952446117
---

<!-- 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 Ckb - Razhan Hameed

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3825
- Wer: 33.2193

## 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: 64
- eval_batch_size: 32
- 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: 12000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1693        | 2.49  | 1000  | 0.2060          | 39.1265 |
| 0.0722        | 4.98  | 2000  | 0.2124          | 36.3173 |
| 0.0127        | 7.46  | 3000  | 0.2736          | 36.5568 |
| 0.008         | 9.95  | 4000  | 0.3131          | 35.7015 |
| 0.0032        | 12.44 | 5000  | 0.3434          | 35.3936 |
| 0.0028        | 14.93 | 6000  | 0.3453          | 35.9258 |
| 0.003         | 17.41 | 7000  | 0.3558          | 34.9565 |
| 0.0022        | 19.9  | 8000  | 0.3593          | 34.2722 |
| 0.0016        | 22.39 | 9000  | 0.3639          | 34.3369 |
| 0.0015        | 24.88 | 10000 | 0.3785          | 34.0062 |
| 0.0009        | 27.36 | 11000 | 0.3915          | 34.2951 |
| 0.0001        | 29.85 | 12000 | 0.3825          | 33.2193 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2