---
language:
- sr
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Serbian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13
      type: mozilla-foundation/common_voice_13_0
      config: sr
      split: test
      args: sr
    metrics:
    - name: Wer
      type: wer
      value: 17.41963509991312
---

<!-- 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 Serbian

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4671
- Wer Ortho: 27.4565
- Wer: 17.4196

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 2500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.1403        | 1.44  | 250  | 0.2809          | 28.8913   | 19.2224 |
| 0.0664        | 2.87  | 500  | 0.2858          | 27.3696   | 17.9626 |
| 0.0315        | 4.31  | 750  | 0.3152          | 27.9348   | 17.4631 |
| 0.0174        | 5.75  | 1000 | 0.3578          | 28.1522   | 17.9844 |
| 0.0067        | 7.18  | 1250 | 0.4018          | 27.9130   | 17.9626 |
| 0.0015        | 8.62  | 1500 | 0.4535          | 28.6739   | 17.5717 |
| 0.0008        | 10.06 | 1750 | 0.4558          | 27.2174   | 17.1807 |
| 0.0005        | 11.49 | 2000 | 0.4585          | 27.4348   | 17.4848 |
| 0.0005        | 12.93 | 2250 | 0.4651          | 27.3478   | 17.3979 |
| 0.0005        | 14.37 | 2500 | 0.4671          | 27.4565   | 17.4196 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3