---
language:
- sl
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 Sl - Padajno
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13
      type: mozilla-foundation/common_voice_13_0
      config: sl
      split: test
      args: sl
    metrics:
    - name: Wer
      type: wer
      value: 25.936967632027258
---

<!-- 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 Sl - Padajno

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: 0.3707
- Wer Ortho: 28.2066
- Wer: 25.9370

## 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: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 600
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.9497        | 0.6135 | 100  | 0.8683          | 37.6703   | 35.8745 |
| 0.171         | 1.2270 | 200  | 0.3742          | 33.4847   | 31.2039 |
| 0.1841        | 1.8405 | 300  | 0.3407          | 31.0585   | 28.7337 |
| 0.0592        | 2.4540 | 400  | 0.3492          | 29.5545   | 27.1153 |
| 0.0434        | 3.0675 | 500  | 0.3624          | 29.7106   | 27.2572 |
| 0.027         | 3.6810 | 600  | 0.3707          | 28.2066   | 25.9370 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1