---
language:
- sr
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small Sr JV
  results: []
---

<!-- 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 Sr JV

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Juzne Vesti dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8988
- Wer Ortho: 0.4591
- Wer: 0.3415

## Model description

Dataset Juzne vesti is published by

Rupnik, Peter and Ljubešić, Nikola, 2022,\
  ASR training dataset for Serbian JuzneVesti-SR v1.0, Slovenian language resource repository CLARIN.SI, ISSN 2820-4042,\
  http://hdl.handle.net/11356/1679.

## 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.5956        | 0.74  | 500  | 0.8063          | 0.4794    | 0.3674 |
| 0.4401        | 1.48  | 1000 | 0.7975          | 0.4574    | 0.3423 |
| 0.3029        | 2.22  | 1500 | 0.7821          | 0.4512    | 0.3392 |
| 0.3016        | 2.96  | 2000 | 0.7828          | 0.4497    | 0.3318 |
| 0.2372        | 3.7   | 2500 | 0.8254          | 0.4503    | 0.3335 |
| 0.1762        | 4.44  | 3000 | 0.8402          | 0.4505    | 0.3381 |
| 0.1414        | 5.18  | 3500 | 0.8945          | 0.4584    | 0.3418 |
| 0.1326        | 5.92  | 4000 | 0.8988          | 0.4591    | 0.3415 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1