---
language:
- sr
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Serbian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 sr
      type: mozilla-foundation/common_voice_11_0
      config: sr
      split: test
      args: sr
    metrics:
    - name: Wer
      type: wer
      value: 22.905706191825175
---

<!-- 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 mozilla-foundation/common_voice_11_0 sr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5670
- Wer: 22.9057

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

The model was trained on the training + validation splits of the Serbian split of the Common Voice dataset and evaluated on the test split of the Serbian split from the Common Voice dataset.

## 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: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4257        | 5.0   | 100  | 0.4377          | 32.4160 |
| 0.0779        | 10.0  | 200  | 0.3928          | 23.7556 |
| 0.0108        | 15.0  | 300  | 0.4856          | 23.4318 |
| 0.0104        | 20.0  | 400  | 0.5637          | 25.4958 |
| 0.0069        | 25.0  | 500  | 0.5289          | 23.1485 |
| 0.0022        | 30.0  | 600  | 0.5670          | 22.9057 |
| 0.0012        | 35.0  | 700  | 0.5746          | 23.0271 |
| 0.0006        | 40.0  | 800  | 0.5810          | 23.1890 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2